From fdab6721125bd2305e791e503134676d41a94093 Mon Sep 17 00:00:00 2001 From: yao Date: Wed, 8 Oct 2025 18:20:02 -0700 Subject: [PATCH 01/10] Working PID loop with simulated world --- dripline/extensions/pid_loop/PID_Tuner.ipynb | 786 + .../pid_loop/PID_Tuner_YAML_accurate.ipynb | 242452 +++++++++++++++ dripline/extensions/pid_loop/__init__.py | 5 + .../pid_log_2025-10-07T06:59:08.867854.csv | 250 + .../pid_log_2025-10-07T16:13:56.263293.csv | 740 + .../pid_log_2025-10-07T17:31:44.320879.csv | 60 + .../pid_log_2025-10-07T17:33:12.633873.csv | 10 + .../pid_log_2025-10-07T17:40:42.156692.csv | 600 + .../pid_log_2025-10-07T18:10:54.356123.csv | 180 + .../pid_log_2025-10-07T19:10:19.113527.csv | 450 + .../pid_log_2025-10-07T19:39:54.964941.csv | 150 + .../pid_log_2025-10-07T19:48:26.640497.csv | 540 + .../pid_log_2025-10-08T04:49:54.764355.csv | 300 + .../pid_log_2025-10-08T04:58:44.998736.csv | 50 + .../pid_log_2025-10-08T05:00:58.170887.csv | 130 + 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dripline/extensions/pid_loop_tester/pid_loop_tester_v2.py diff --git a/dripline/extensions/pid_loop/PID_Tuner.ipynb b/dripline/extensions/pid_loop/PID_Tuner.ipynb new file mode 100644 index 0000000..2580eac --- /dev/null +++ b/dripline/extensions/pid_loop/PID_Tuner.ipynb @@ -0,0 +1,786 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "ba795d92", + "metadata": {}, + "source": [ + "\n", + "# PID Tuner (Standalone Notebook)\n", + "\n", + "This notebook is a single-file, **standalone** environment to test PID parameters efficiently. \n", + "It bundles:\n", + "- A minimal in-memory \"Service\" (mock of `dripline.core.Service`) so no external deps are required.\n", + "- Your **PID controller** logic (positional PID with anti-windup hooks, derivative-on-measurement, optional baseline).\n", + "- A simple **thermal plant** simulator (1R-1C model) that maps a throttle to heater power.\n", + "- A `run_sim(...)` helper to sweep gains quickly and plot PV/SP/throttle.\n", + "- Optional CSV export of a simulation run.\n", + "\n", + "> Tip: Edit parameters in the **\"Quick start: run a simulation\"** cell and re-run.\n" + ] + }, + { + "cell_type": "markdown", + "id": "b22de803", + "metadata": {}, + "source": [] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "b3f55b46", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'/bin/python3'" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import sys\n", + "sys.executable\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "3d5e01ca", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "# --- Imports & helpers ---\n", + "from __future__ import annotations\n", + "\n", + "import math\n", + "import time\n", + "import datetime\n", + "from dataclasses import dataclass\n", + "from typing import Optional, Dict, Any, Tuple, List\n", + "\n", + "import csv\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# make plots a bit crisper in notebooks\n", + "%config InlineBackend.figure_format = 'retina'\n", + "\n", + "def clamp(x: float, lo: float, hi: float) -> float:\n", + " return lo if x < lo else hi if x > hi else x\n", + "\n", + "class ThrowReply(Exception):\n", + " pass\n" + ] + }, + { + "cell_type": "markdown", + "id": "ead95cfe", + "metadata": {}, + "source": [ + "## Minimal in-memory `Service` mock" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "0bdb11b1", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "class Service:\n", + " \"\"\"\n", + " Minimal drop-in replacement for dripline.core.Service with only get/set APIs.\n", + " Uses a shared in-memory key-value store (dict of dicts) with a configurable 'read_field'.\n", + " \"\"\"\n", + " _GLOBAL_STORE: Dict[str, Dict[str, Any]] = {}\n", + "\n", + " def __init__(self, *, read_field: str = \"value_cal\", store: Optional[Dict[str, Dict[str, Any]]] = None, **kwargs):\n", + " self._read_field = read_field\n", + " # allow passing an external store so controller + tester share the same memory\n", + " if store is None:\n", + " self._store = Service._GLOBAL_STORE\n", + " else:\n", + " self._store = store\n", + "\n", + " def get(self, key: str) -> Dict[str, Any]:\n", + " return self._store.get(key, {})\n", + "\n", + " def set(self, key: str, value: Any) -> Dict[str, Any]:\n", + " d = self._store.get(key)\n", + " if d is None:\n", + " d = {}\n", + " self._store[key] = d\n", + " d[self._read_field] = value\n", + " # attach a timestamp for realism\n", + " d[\"timestamp\"] = datetime.datetime.utcnow().strftime('%d/%m/%y %H:%M:%S.%f')\n", + " return d\n" + ] + }, + { + "cell_type": "markdown", + "id": "4b40739d", + "metadata": {}, + "source": [ + "## PID Controller" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "d53dcd8b", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "class PidController(Service):\n", + " \"\"\"\n", + " PID control loop (positional PID form with optional baseline offset).\n", + "\n", + " e = SP - PV\n", + " u = u_offset + Kp*e + Ki*integral(e dt) - Kd*d(PV)/dt\n", + "\n", + " Public surface mirrors your existing class enough to drop-in here.\n", + " Networking/timeouts/threads are removed for notebook simplicity; the logic is the same.\n", + " \"\"\"\n", + "\n", + " def __init__(self,\n", + " input_channel: str,\n", + " output_channel: str,\n", + " check_channel: str,\n", + " status_channel: str,\n", + " payload_field: str = 'value_cal',\n", + " tolerance: float = 0.01,\n", + " target_value: float = 85.0,\n", + " proportional: float = 0.0,\n", + " integral: float = 0.0,\n", + " differential: float = 0.0,\n", + " maximum_out: float = 1.0,\n", + " minimum_out: float = 0.0,\n", + " delta_out_min: float = 0.001,\n", + " enable_offset_term: bool = False,\n", + " minimum_elapsed_time: float = 0.0,\n", + " # notebook-friendly knobs\n", + " integral_limit: Optional[float] = None,\n", + " derivative_smoothing: float = 0.0,\n", + " max_settle_wait_s: float = 0.5,\n", + " u_offset_baseline: float = 0.0,\n", + " store: Optional[Dict[str, Dict[str, Any]]] = None,\n", + " **kwargs):\n", + "\n", + " super().__init__(read_field=payload_field, store=store, **kwargs)\n", + "\n", + " self._input_channel = input_channel\n", + " self._set_channel = output_channel\n", + " self._check_channel = check_channel\n", + " self._status_channel = status_channel\n", + " self.payload_field = payload_field\n", + " self.tolerance = float(tolerance)\n", + "\n", + " self._target_value = float(target_value)\n", + " self.Kproportional = float(proportional)\n", + " self.Kintegral = float(integral)\n", + " self.Kdifferential = float(differential)\n", + "\n", + " self.max_current = float(maximum_out)\n", + " self.min_current = float(minimum_out)\n", + " self.min_current_change = float(delta_out_min)\n", + "\n", + " self.enable_offset_term = bool(enable_offset_term)\n", + " self.u_offset_baseline = float(u_offset_baseline)\n", + " self.max_settle_wait_s = float(max_settle_wait_s)\n", + "\n", + " self.minimum_elapsed_time = max(0.0, float(minimum_elapsed_time))\n", + "\n", + " self._integral = 0.0\n", + " self._int_limit = None if integral_limit is None else abs(float(integral_limit))\n", + " self._alpha_d = clamp(float(derivative_smoothing), 0.0, 1.0)\n", + " self._ema_dpvdt = 0.0\n", + " self._last_data = {'value': None, 'time': None}\n", + " self._force_reprocess = False\n", + "\n", + " # initialize status + old_current sensibly if not present\n", + " if self.get(self._status_channel).get(self.payload_field) is None:\n", + " self.set(self._status_channel, \"enabled\")\n", + "\n", + " self.__validate_status()\n", + " try:\n", + " self._old_current = self.__get_current()\n", + " except Exception:\n", + " self._old_current = 0.0\n", + " self.set(self._check_channel, self._old_current)\n", + "\n", + " # ---- Public surface ----\n", + " @property\n", + " def target_value(self) -> float:\n", + " return self._target_value\n", + "\n", + " @target_value.setter\n", + " def target_value(self, value: float) -> None:\n", + " self._target_value = float(value)\n", + " self._integral = 0.0\n", + " self._force_reprocess = True\n", + "\n", + " def set_current(self, value: float) -> None:\n", + " # write both set_channel and check_channel in this notebook (no hardware lag model here)\n", + " self.set(self._set_channel, float(value))\n", + " self.set(self._check_channel, float(value))\n", + "\n", + " def process_new_value(self, value: float, timestamp: datetime.datetime) -> float:\n", + " \"\"\"Run one PID step. Returns the new command `u`.\"\"\"\n", + " last_time = self._last_data['time']\n", + " last_value = self._last_data['value']\n", + "\n", + " if last_time is None:\n", + " self._last_data = {'value': float(value), 'time': timestamp}\n", + " return self._old_current\n", + "\n", + " dt = (timestamp - last_time).total_seconds()\n", + " if dt <= 0:\n", + " dt = max(self.minimum_elapsed_time, 1e-6)\n", + " if dt < self.minimum_elapsed_time and not self._force_reprocess:\n", + " return self._old_current\n", + " self._force_reprocess = False\n", + "\n", + " # error + integral\n", + " e = self._target_value - float(value)\n", + " self._integral += e * dt\n", + " if self._int_limit is not None:\n", + " self._integral = clamp(self._integral, -self._int_limit, self._int_limit)\n", + "\n", + " # derivative on measurement\n", + " if last_value is None:\n", + " d_pv_dt = 0.0\n", + " else:\n", + " raw_d = (float(value) - float(last_value)) / dt\n", + " d_pv_dt = raw_d\n", + " # TODO: Check this\n", + " # self._ema_dpvdt = self._alpha_d * self._ema_dpvdt + (1 - self._alpha_d) * raw_d\n", + " # d_pv_dt = self._ema_dpvdt if self._alpha_d > 0 else raw_d\n", + "\n", + " self._last_data = {'value': float(value), 'time': timestamp}\n", + "\n", + " baseline = (self._old_current if self.enable_offset_term else 0.0) + self.u_offset_baseline\n", + " delta_terms = self.Kproportional * e + self.Kintegral * self._integral - self.Kdifferential * d_pv_dt\n", + " u = baseline + delta_terms\n", + "\n", + " u_sat = clamp(u, self.min_current, self.max_current)\n", + " if u != u_sat and self.Kintegral > 0.0:\n", + " # back-calculation\n", + " self._integral += (u_sat - u) / self.Kintegral\n", + " # TODO: Check this\n", + " # if self._int_limit is not None:\n", + " # self._integral = clamp(self._integral, -self._int_limit, self._int_limit)\n", + " u = u_sat\n", + " else:\n", + " u = u_sat\n", + "\n", + " if abs(u - self._old_current) < self.min_current_change:\n", + " return self._old_current\n", + "\n", + " self.set_current(u)\n", + " self._old_current = u\n", + " return u\n", + "\n", + " # ---- Private helpers ----\n", + " def __get_current(self) -> float:\n", + " d = self.get(self._check_channel)\n", + " if not d:\n", + " raise ThrowReply(\"current read failed\")\n", + " v = d.get(self.payload_field)\n", + " return float(v)\n", + "\n", + " def __validate_status(self) -> None:\n", + " value = self.get(self._status_channel).get(self.payload_field)\n", + " if not value:\n", + " raise ThrowReply(f\"Invalid status on {self._status_channel}\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "52792cfc", + "metadata": {}, + "source": [ + "## Thermal plant (1R-1C) — `PidLoopTester` analogue" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "a6997262", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "class PidLoopTester(Service):\n", + " \"\"\"\n", + " 1R-1C thermal model with a throttle->power map.\n", + "\n", + " C dT/dt = P_heater(t) - (T - T_env)/R_th + D(t)\n", + " throttle in 'current' mode is Amps; power = eta * R_heater * I^2\n", + " \"\"\"\n", + " def __init__(self,\n", + " time_step=0.1,\n", + " T0=40.0,\n", + " C=10.0,\n", + " R_th=1.0,\n", + " T_env=40.0,\n", + " throttle_mode='current', # 'current' or 'power'\n", + " I_max=2.5,\n", + " R_heater=6.0,\n", + " eta=0.95,\n", + " P_max=100.0,\n", + " read_field='value_cal',\n", + " throttle_endpoint=\"throttle\",\n", + " sensor_endpoint=\"sensor\",\n", + " store: Optional[Dict[str, Dict[str, Any]]] = None,\n", + " **kwargs):\n", + " super().__init__(read_field=read_field, store=store, **kwargs)\n", + "\n", + " self.dt = float(time_step)\n", + " self.C = float(C)\n", + " self.Rth = float(R_th)\n", + " self.Tenv = float(T_env)\n", + "\n", + " self.mode = str(throttle_mode).lower()\n", + " self.Imax = float(I_max)\n", + " self.Rheater = float(R_heater)\n", + " self.eta = float(eta)\n", + " self.Pmax = float(P_max)\n", + "\n", + " self.throttle_key = throttle_endpoint\n", + " self.sensor_key = sensor_endpoint\n", + "\n", + " # init endpoints\n", + " self.set(self.sensor_key, float(T0))\n", + " self.set(self.throttle_key, 0.0)\n", + "\n", + " self.t = 0.0\n", + "\n", + " # I/O\n", + " def get_sensor_value(self) -> float:\n", + " return float(self.get(self.sensor_key).get(self._read_field, 0.0))\n", + "\n", + " def set_sensor_value(self, value: float) -> None:\n", + " self.set(self.sensor_key, float(value))\n", + "\n", + " def get_throttle_value(self) -> float:\n", + " return float(self.get(self.throttle_key).get(self._read_field, 0.0))\n", + "\n", + " def set_throttle_value(self, value: float) -> None:\n", + " self.set(self.throttle_key, float(value))\n", + "\n", + " # mapping\n", + " def _power_from_throttle(self, throttle_value: float) -> float:\n", + " if self.mode == 'current':\n", + " I = clamp(float(throttle_value), 0.0, self.Imax)\n", + " return self.eta * self.Rheater * (I**2)\n", + " elif self.mode == 'power':\n", + " return clamp(float(throttle_value), 0.0, self.Pmax)\n", + " else:\n", + " raise ThrowReply(\"throttle_mode must be 'current' or 'power'\")\n", + "\n", + " def external_disturbance(self, t: float) -> float:\n", + " # customize as needed\n", + " if 10.0 < t < 15.0:\n", + " return -1.0\n", + " elif 20.0 < t < 25.0:\n", + " return +0.5\n", + " elif t > 40.0:\n", + " return 0.2 * math.sin(t)\n", + " else:\n", + " return 0.0\n", + "\n", + " def step(self) -> None:\n", + " T = self.get_sensor_value()\n", + " throttle = self.get_throttle_value()\n", + " P_heater = self._power_from_throttle(throttle)\n", + " P_loss = (T - self.Tenv) / self.Rth\n", + " D = self.external_disturbance(self.t)\n", + " dT_dt = (P_heater - P_loss + D) / self.C\n", + " T_new = T + self.dt * dT_dt\n", + " self.set_sensor_value(T_new)\n", + " self.t += self.dt\n" + ] + }, + { + "cell_type": "markdown", + "id": "41db1673", + "metadata": {}, + "source": [ + "## Simulation harness: `run_sim(...)`" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "e12346cc", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "def run_sim(\n", + " duration_s: float = 60.0,\n", + " controller_period_s: float = 0.1,\n", + " # plant\n", + " T0: float = 40.0, \n", + " C: float = 10.0, \n", + " R_th: float = 1.0, \n", + " T_env: float = 40.0,\n", + " I_0: float = 0.0,\n", + " throttle_mode: str = \"current\", \n", + " I_max: float = 2.5, \n", + " R_heater: float = 6.0, \n", + " eta: float = 0.95, \n", + " P_max: float = 100.0,\n", + " dt: float = 0.05,\n", + " # controller\n", + " SP: float = 85.0, # target temperature\n", + " Kp: float = 0.01, # proportional gain\n", + " Ki: float = 0.002, # integral gain\n", + " Kd: float = 0.0, # derivative gain\n", + " u_min: float = 0.0, # minimum throttle\n", + " u_max: float = 2.5, # maximum throttle\n", + " du_min: float = 1e-3, # minimum change in throttle\n", + " derivative_smoothing: float = 0.0, # derivative smoothing\n", + " int_limit: Optional[float] = None, # integral limit\n", + " enable_offset_term: bool = False, # enable offset term\n", + " baseline_offset: float = 0.0, # baseline offset\n", + " # logging/export\n", + " csv_path: Optional[str] = None, # path to save CSV\n", + " ) -> pd.DataFrame:\n", + " \"\"\"\n", + " Run a closed-loop simulation and return a DataFrame with time, PV, SP, throttle.\n", + " Optionally writes a CSV if csv_path is given.\n", + " \"\"\"\n", + " # shared store\n", + " store: Dict[str, Dict[str, Any]] = {}\n", + " read_field = \"value_cal\"\n", + " sensor_key = \"sensor_value.sensor\"\n", + " throttle_key = \"actuator.throttle\"\n", + " check_key = \"actuator.readback\"\n", + " status_key = \"status.enabled\"\n", + "\n", + " # seed status + readback\n", + " store[status_key] = {read_field: \"enabled\"}\n", + " store[check_key] = {read_field: 0.0}\n", + "\n", + " # plant + controller\n", + " plant = PidLoopTester(\n", + " time_step=dt, T0=T0, C=C, R_th=R_th, T_env=T_env,\n", + " throttle_mode=throttle_mode, I_max=I_max, R_heater=R_heater, eta=eta, P_max=P_max,\n", + " read_field=read_field, throttle_endpoint=throttle_key, sensor_endpoint=sensor_key, store=store\n", + " )\n", + "\n", + " pid = PidController(\n", + " input_channel=sensor_key, output_channel=throttle_key, check_channel=check_key, status_channel=status_key,\n", + " payload_field=read_field, tolerance=0.01, target_value=SP, proportional=Kp, integral=Ki, differential=Kd,\n", + " maximum_out=u_max, minimum_out=u_min, delta_out_min=du_min, enable_offset_term=enable_offset_term,\n", + " minimum_elapsed_time=controller_period_s, derivative_smoothing=derivative_smoothing,\n", + " integral_limit=int_limit, u_offset_baseline=baseline_offset, store=store\n", + " )\n", + "\n", + " # sim loop\n", + " t = 0.0\n", + " next_ctl = 0.0\n", + " rows: List[Tuple[float, float, float, float]] = []\n", + " while t <= duration_s + 1e-12:\n", + " # controller tick\n", + " if t >= next_ctl:\n", + " PV = plant.get_sensor_value()\n", + " ts = datetime.datetime.utcnow()\n", + " u = pid.process_new_value(PV, ts)\n", + " plant.set_throttle_value(u) # write the command\n", + " next_ctl += controller_period_s\n", + "\n", + " # plant evolves\n", + " plant.step()\n", + "\n", + " # log\n", + " rows.append((t, plant.get_sensor_value(), SP, plant.get_throttle_value()))\n", + " t += dt\n", + " time.sleep(dt) \n", + "\n", + " import pandas as pd\n", + " df = pd.DataFrame(rows, columns=[\"time_s\", \"PV\", \"SP\", \"throttle\"])\n", + "\n", + " if csv_path:\n", + " df.to_csv(csv_path, index=False)\n", + "\n", + " return df\n" + ] + }, + { + "cell_type": "markdown", + "id": "da0873df", + "metadata": {}, + "source": [ + "## Quick start: run a simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "203e908d", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ], + "text/plain": [ + " time_s PV SP throttle\n", + "0 0.00 40.0 85.0 0.0\n", + "1 0.05 40.0 85.0 0.0\n", + "2 0.10 40.0 85.0 0.0\n", + "3 0.15 40.0 85.0 0.0\n", + "4 0.20 40.0 85.0 0.0" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "# Example: mild heating from 40 K toward 85 K using current mode (I_max=2.5 A)\n", + "df = run_sim(\n", + " duration_s=90.0,\n", + " controller_period_s=0.1,\n", + " T0=40.0, C=12.0, R_th=1.2, T_env=40.0,\n", + " throttle_mode=\"current\", I_max=2.5, R_heater=6.0, eta=0.95,\n", + " dt=0.05,\n", + " SP=85.0, Kp=0.12, Ki=0.02, Kd=0.0,\n", + " u_min=0.0, u_max=2.5, du_min=0.001,\n", + " derivative_smoothing=0.2,\n", + " int_limit=200.0,\n", + " enable_offset_term=False,\n", + " baseline_offset=0.0,\n", + " csv_path=None\n", + ")\n", + "\n", + "# Plot PV vs SP\n", + "plt.figure()\n", + "plt.plot(df[\"time_s\"], df[\"PV\"], label=\"PV (sensor)\")\n", + "plt.plot(df[\"time_s\"], df[\"SP\"], linestyle=\"--\", label=\"SP (setpoint)\")\n", + "plt.xlabel(\"Time [s]\")\n", + "plt.ylabel(\"Temperature [K]\")\n", + "plt.title(\"PID: Sensor vs Setpoint\")\n", + "plt.legend()\n", + "plt.grid(True)\n", + "plt.show()\n", + "\n", + "# Plot throttle\n", + "plt.figure()\n", + "plt.plot(df[\"time_s\"], df[\"throttle\"], label=\"Throttle (A or W)\")\n", + "plt.xlabel(\"Time [s]\")\n", + "plt.ylabel(\"Throttle\")\n", + "plt.title(\"PID: Actuator Command\")\n", + "plt.legend()\n", + "plt.grid(True)\n", + "plt.show()\n", + "\n", + "df.head()\n" + ] + }, + { + "cell_type": "markdown", + "id": "7c57f05d", + "metadata": {}, + "source": [ + "## Optional: simple metrics" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "f308121a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'overshoot_abs': 0.0, 'settling_time_s': None}" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "def analyze_run(df, tol=0.5, window_s=5.0):\n", + " \"\"\"\n", + " Compute a rough settling time and overshoot.\n", + " - tol: absolute tolerance band around SP to consider 'settled'\n", + " - window_s: must stay within band for this trailing window\n", + " \"\"\"\n", + " sp = df[\"SP\"].iloc[-1]\n", + " t = df[\"time_s\"].values\n", + " pv = df[\"PV\"].values\n", + " # overshoot\n", + " overshoot = max(0.0, (pv.max() - sp))\n", + "\n", + " # settling time\n", + " settle_t = None\n", + " import numpy as np\n", + " for i in range(len(t)):\n", + " t0 = t[i]\n", + " mask = (t >= t0) & (t <= t0 + window_s)\n", + " if mask.sum() == 0:\n", + " continue\n", + " band_ok = (np.abs(pv[mask] - sp) <= tol).all()\n", + " if band_ok:\n", + " settle_t = t0\n", + " break\n", + "\n", + " return {\"overshoot_abs\": overshoot, \"settling_time_s\": settle_t}\n", + "\n", + "analyze_run(df)\n" + ] + }, + { + "cell_type": "markdown", + "id": "c14cac3c", + "metadata": {}, + "source": [ + "## Export to CSV (optional)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8a1f7be0", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "# Example of saving the last run:\n", + "# df.to_csv(\"pid_last_run.csv\", index=False)\n", + "# print(\"Saved to pid_last_run.csv\")\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/dripline/extensions/pid_loop/PID_Tuner_YAML_accurate.ipynb b/dripline/extensions/pid_loop/PID_Tuner_YAML_accurate.ipynb new file mode 100644 index 0000000..78f1ad1 --- /dev/null +++ b/dripline/extensions/pid_loop/PID_Tuner_YAML_accurate.ipynb @@ -0,0 +1,242452 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "b6af4550", + "metadata": {}, + "source": [ + "\n", + "# PID Tuner (YAML-accurate)\n", + "\n", + "This notebook mirrors your Dripline YAML:\n", + "- `minimum_elapsed_time = 1.0 s` (PID updates at most once per second)\n", + "- Polling at `controller_period_s = 0.1 s`\n", + "- Derivative EMA smoothing with `derivative_smoothing = 0.9`\n", + "- Channels: `check_channel = throttle`, `status_channel = sensor`\n", + "- Plant `dt = 0.1 s` and real-time `time.sleep(dt)`\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "3a4f5059", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "from __future__ import annotations\n", + "\n", + "import math, time, datetime\n", + "from typing import Optional, Dict, Any, Tuple, List\n", + "from pathlib import Path\n", + "\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "\n", + "import csv\n", + "%config InlineBackend.figure_format = 'retina'\n", + "\n", + "def clamp(x: float, lo: float, hi: float) -> float:\n", + " return lo if x < lo else hi if x > hi else x\n", + "\n", + "class ThrowReply(Exception):\n", + " pass\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "e79829d6", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "class Service:\n", + " _GLOBAL_STORE: Dict[str, Dict[str, Any]] = {}\n", + "\n", + " def __init__(self, *, read_field: str = \"value_cal\", store: Optional[Dict[str, Dict[str, Any]]] = None, **kwargs):\n", + " self._read_field = read_field\n", + " self._store = store if store is not None else Service._GLOBAL_STORE\n", + "\n", + " def get(self, key: str) -> Dict[str, Any]:\n", + " return self._store.get(key, {})\n", + "\n", + " def set(self, key: str, value: Any) -> Dict[str, Any]:\n", + " d = self._store.get(key)\n", + " if d is None:\n", + " d = {}\n", + " self._store[key] = d\n", + " d[self._read_field] = value\n", + " d[\"timestamp\"] = datetime.datetime.utcnow().strftime('%d/%m/%y %H:%M:%S.%f')\n", + " return d\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "61c63d4b", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "class PidController(Service):\n", + " def __init__(self,\n", + " input_channel: str,\n", + " output_channel: str,\n", + " check_channel: str,\n", + " status_channel: str,\n", + " payload_field: str = 'value_cal',\n", + " tolerance: float = 0.01,\n", + " target_value: float = 85.0,\n", + " proportional: float = 0.01,\n", + " integral: float = 0.002,\n", + " differential: float = 0.0,\n", + " maximum_out: float = 2.5,\n", + " minimum_out: float = 0.0,\n", + " delta_out_min: float = 0.001,\n", + " enable_offset_term: bool = False,\n", + " minimum_elapsed_time: float = 1.0,\n", + " integral_limit: Optional[float] = 200.0,\n", + " derivative_smoothing: float = 0.9,\n", + " max_settle_wait_s: float = 3.0,\n", + " u_offset_baseline: float = 0.0,\n", + " store: Optional[Dict[str, Dict[str, Any]]] = None,\n", + " **kwargs):\n", + "\n", + " super().__init__(read_field=payload_field, store=store, **kwargs)\n", + "\n", + " self._input_channel = input_channel\n", + " self._set_channel = output_channel\n", + " self._check_channel = check_channel\n", + " self._status_channel = status_channel\n", + " self.payload_field = payload_field\n", + " self.tolerance = float(tolerance)\n", + "\n", + " self._target_value = float(target_value)\n", + " self.Kproportional = float(proportional)\n", + " self.Kintegral = float(integral)\n", + " self.Kdifferential = float(differential)\n", + "\n", + " self.max_current = float(maximum_out)\n", + " self.min_current = float(minimum_out)\n", + " self.min_current_change = float(delta_out_min)\n", + "\n", + " self.enable_offset_term = bool(enable_offset_term)\n", + " self.u_offset_baseline = float(u_offset_baseline)\n", + " self.max_settle_wait_s = float(max_settle_wait_s)\n", + "\n", + " self.minimum_elapsed_time = max(0.0, float(minimum_elapsed_time))\n", + "\n", + " self._integral = 0.0\n", + " self._int_limit = None if integral_limit is None else abs(float(integral_limit))\n", + " self._alpha_d = clamp(float(derivative_smoothing), 0.0, 1.0)\n", + " self._ema_dpvdt = 0.0\n", + " self._last_data = {'value': None, 'time': None}\n", + " self._force_reprocess = False\n", + "\n", + " self._log_filename = f\"pid_log_tuner_{datetime.datetime.now().isoformat()}.csv\"\n", + "\n", + " if not self.get(self._status_channel):\n", + " self.set(self._status_channel, 40.0)\n", + " if not self.get(self._check_channel):\n", + " self.set(self._check_channel, 0.0)\n", + "\n", + " self.__validate_status()\n", + " try:\n", + " self._old_current = self.__get_current()\n", + " except Exception:\n", + " self._old_current = 0.0\n", + " self.set(self._check_channel, self._old_current)\n", + "\n", + " @property\n", + " def target_value(self) -> float:\n", + " return self._target_value\n", + "\n", + " @target_value.setter\n", + " def target_value(self, value: float) -> None:\n", + " self._target_value = float(value)\n", + " self._integral = 0.0\n", + " self._force_reprocess = True\n", + "\n", + " def set_current(self, value: float) -> None:\n", + " self.set(self._set_channel, float(value))\n", + " self.set(self._check_channel, float(value))\n", + "\n", + " def _log_append(self, timestamp: datetime.datetime, pv: float, sp: float, u: float) -> None:\n", + " row = (timestamp.isoformat(), float(pv), float(sp), float(u) if u is not None else float(\"nan\"))\n", + " self._log_data.append(row)\n", + " mode = \"a\"\n", + " # try:\n", + " with open(self._log_filename, mode, newline=\"\") as f:\n", + " writer = csv.writer(f)\n", + " writer.writerows(row)\n", + " # print(f\"Appended {len(row)} rows to {self._log_filename}\")\n", + " # except Exception as ex:\n", + " # print(f\"Failed flushing CSV: {ex}\")\n", + "\n", + " def process_new_value(self, value: float, timestamp: datetime.datetime) -> float:\n", + " last_time = self._last_data['time']\n", + " last_value = self._last_data['value']\n", + "\n", + " if last_time is None:\n", + " self._last_data = {'value': float(value), 'time': timestamp}\n", + " return self._old_current\n", + "\n", + " dt = timestamp - last_time #.total_seconds()\n", + " if dt <= 0:\n", + " print(f\"dt is less than 0: {dt}\")\n", + " dt = max(self.minimum_elapsed_time, 1e-6)\n", + "\n", + " if dt < self.minimum_elapsed_time and not self._force_reprocess:\n", + " print(f\"not enough time has elasped: {dt}[{self.minimum_elapsed_time}]\")\n", + " return self._old_current\n", + " \n", + " self._force_reprocess = False\n", + "\n", + " # --- 2) Error\n", + " e = self._target_value - float(value)\n", + " print(f\"e: {e}\")\n", + " self._integral += e * dt\n", + "\n", + " # --- 3) Integral with optional clamping\n", + " if self._int_limit is not None:\n", + " self._integral = clamp(self._integral, -self._int_limit, self._int_limit)\n", + "\n", + " # --- 4) Derivative on measurement (reduces setpoint kick)\n", + " if last_value is None:\n", + " d_pv_dt = 0.0\n", + " else:\n", + " raw_d = (float(value) - float(last_value)) / dt\n", + " d_pv_dt = raw_d\n", + " # TODO: Check this\n", + " # self._ema_dpvdt = self._alpha_d * self._ema_dpvdt + (1 - self._alpha_d) * raw_d\n", + " # d_pv_dt = self._ema_dpvdt if self._alpha_d > 0 else raw_d\n", + "\n", + " # --- Update last sample after derivative calc\n", + " self._last_data = {'value': float(value), 'time': timestamp}\n", + "\n", + " baseline = (self._old_current if self.enable_offset_term else 0.0) + self.u_offset_baseline\n", + " delta_terms = (self.Kproportional * e \n", + " + self.Kintegral * self._integral \n", + " - self.Kdifferential * d_pv_dt)\n", + " new_current = baseline + delta_terms\n", + "\n", + " new_current_sat = clamp(new_current, self.min_current, self.max_current)\n", + " new_current = new_current_sat\n", + " # if u != u_sat and self.Kintegral > 0.0:\n", + " # Back-calc: adjust integral to make effective output equal the sat value\n", + " # self._integral += (u_sat - u) / self.Kintegral\n", + " # if self._int_limit is not None:\n", + " # self._integral = clamp(self._integral, -self._int_limit, self._int_limit)\n", + " # u = u_sat\n", + " # else:\n", + " # u = u_sat\n", + "\n", + " if abs(new_current - self._old_current) < self.min_current_change:\n", + " print(\"current change less than min delta\")\n", + " print(f\"old[new] are: {self._old_current}[{new_current}]\")\n", + " self._log_append(timestamp, value, self._target_value, self._old_current)\n", + " return self._old_current\n", + "\n", + " self.set_current(new_current)\n", + " self._log_append(timestamp, value, self._target_value, new_current)\n", + "\n", + " print(f\"PV={value:.4f} SP={self._target_value:.4f} e={e:.4f} dt={dt:.3f} \"\n", + " f\"u={new_current:.6f} (Kp={self.Kproportional}, Ki={self.Kintegral}, Kd={self.Kdifferential})\")\n", + " self._old_current = new_current\n", + " return new_current\n", + "\n", + " def __get_current(self) -> float:\n", + " d = self.get(self._check_channel)\n", + " if not d:\n", + " raise ThrowReply(\"current read failed\")\n", + " return float(d.get(self.payload_field))\n", + "\n", + " def __validate_status(self) -> None:\n", + " value = self.get(self._status_channel).get(self.payload_field)\n", + " if not value and value != 0:\n", + " raise ThrowReply(f\"Invalid status on {self._status_channel}\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "e5ff351c", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "class PidLoopTester(Service):\n", + " def __init__(self,\n", + " time_step=0.1,\n", + " T0=40.0,\n", + " C=10.0,\n", + " R_th=1.0,\n", + " T_env=40.0,\n", + " throttle_mode='current',\n", + " I_max=3,\n", + " R_heater=6.0,\n", + " eta=0.95,\n", + " P_max=100.0,\n", + " read_field='value_cal',\n", + " throttle_endpoint=\"throttle\",\n", + " sensor_endpoint=\"sensor\",\n", + " store: Optional[Dict[str, Dict[str, Any]]] = None,\n", + " **kwargs):\n", + " super().__init__(read_field=read_field, store=store, **kwargs)\n", + "\n", + " self.dt = float(time_step)\n", + " self.C = float(C)\n", + " self.Rth = float(R_th)\n", + " self.Tenv = float(T_env)\n", + "\n", + " self.mode = str(throttle_mode).lower()\n", + " self.Imax = float(I_max)\n", + " self.Rheater = float(R_heater)\n", + " self.eta = float(eta)\n", + " self.Pmax = float(P_max)\n", + "\n", + " self.throttle_key = throttle_endpoint\n", + " self.sensor_key = sensor_endpoint\n", + "\n", + " self.set(self.sensor_key, float(T0))\n", + " self.set(self.throttle_key, 0.0)\n", + "\n", + " self.t = 0.0\n", + "\n", + " def get_sensor_value(self) -> float:\n", + " return float(self.get(self.sensor_key).get(self._read_field, 0.0))\n", + "\n", + " def set_sensor_value(self, value: float) -> None:\n", + " self.set(self.sensor_key, float(value))\n", + "\n", + " def get_throttle_value(self) -> float:\n", + " return float(self.get(self.throttle_key).get(self._read_field, 0.0))\n", + "\n", + " def set_throttle_value(self, value: float) -> None:\n", + " self.set(self.throttle_key, float(value))\n", + "\n", + " def _power_from_throttle(self, throttle_value: float) -> float:\n", + " if self.mode == 'current':\n", + " I = clamp(float(throttle_value), 0.0, self.Imax)\n", + " return self.eta * self.Rheater * (I**2)\n", + " elif self.mode == 'power':\n", + " return clamp(float(throttle_value), 0.0, self.Pmax)\n", + " else:\n", + " raise ThrowReply(\"throttle_mode must be 'current' or 'power'\")\n", + "\n", + " def external_disturbance(self, t: float) -> float:\n", + " if 10.0 < t < 15.0:\n", + " return -1.0\n", + " elif 20.0 < t < 25.0:\n", + " return +0.5\n", + " elif t > 40.0:\n", + " return 0.2 * math.sin(t)\n", + " else:\n", + " return 0.0\n", + "\n", + " def step(self) -> None:\n", + " T = self.get_sensor_value()\n", + " throttle = self.get_throttle_value()\n", + " P_heater = self._power_from_throttle(throttle)\n", + " P_loss = (T - self.Tenv) / self.Rth\n", + " D = self.external_disturbance(self.t)\n", + " dT_dt = (P_heater - P_loss + D) / self.C\n", + " T_new = T + self.dt * dT_dt\n", + " self.set_sensor_value(T_new)\n", + " self.t += self.dt\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "456a295f", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "def run_sim(\n", + " duration_s: float = 300.0,\n", + " controller_period_s: float = 0.1,\n", + " T0: float = 40.0, \n", + " C: float = 10.0, \n", + " R_th: float = 1.0, \n", + " T_env: float = 40.0,\n", + " # thermal plant parameters\n", + " throttle_mode: str = \"current\", \n", + " I_max: float = 0.3, \n", + " R_heater: float = 6.0, \n", + " eta: float = 0.95, \n", + " P_max: float = 100.0,\n", + " dt: float = 0.1,\n", + " SP: float = 85.0,\n", + " Kp: float = 1.0, \n", + " Ki: float = 0.001, \n", + " Kd: float = 0.0,\n", + " I_min: float = 0.0, \n", + " du_min: float = 0.001,\n", + " derivative_smoothing: float = 0.9,\n", + " int_limit: Optional[float] = 200.0,\n", + " enable_offset_term: bool = False,\n", + " u_offset_baseline: float = 0.0,\n", + " csv_path: Optional[str] = \"./logs/pid_last_run.csv\",\n", + " realtime: bool = True,\n", + " ) -> pd.DataFrame:\n", + "\n", + " store: Dict[str, Dict[str, Any]] = {}\n", + " read_field = \"value_cal\"\n", + " sensor_key = \"sensor\"\n", + " throttle_key = \"throttle\"\n", + " check_key = \"throttle\"\n", + " status_key = \"sensor\"\n", + "\n", + " store[sensor_key] = {read_field: T0}\n", + " store[throttle_key] = {read_field: 0.0}\n", + "\n", + " plant = PidLoopTester(\n", + " time_step=dt, T0=T0, C=C, R_th=R_th, T_env=T_env,\n", + " throttle_mode=throttle_mode, I_max=I_max, R_heater=R_heater, eta=eta, P_max=P_max,\n", + " read_field=read_field, throttle_endpoint=throttle_key, sensor_endpoint=sensor_key, store=store\n", + " )\n", + " \n", + " pid = PidController(\n", + " input_channel=sensor_key, output_channel=throttle_key, check_channel=check_key, status_channel=status_key,\n", + " payload_field=read_field, tolerance=0.01, target_value=SP, proportional=Kp, integral=Ki, differential=Kd,\n", + " maximum_out=I_max, minimum_out=I_min, delta_out_min=du_min, enable_offset_term=enable_offset_term,\n", + " minimum_elapsed_time=1.0, derivative_smoothing=derivative_smoothing,\n", + " integral_limit=int_limit, u_offset_baseline=u_offset_baseline, store=store\n", + " )\n", + " \n", + "\n", + " t = 0.0\n", + " next_ctl = 0.0\n", + " rows: List[Tuple[float, float, float, float]] = []\n", + " start_wall = time.perf_counter()\n", + " while t <= duration_s + 1e-12:\n", + " if t >= next_ctl:\n", + " PV = plant.get_sensor_value()\n", + " ts = datetime.datetime.now(datetime.timezone.utc)\n", + " u = pid.process_new_value(PV, t)\n", + " plant.set_throttle_value(u)\n", + " next_ctl += controller_period_s\n", + " print(f\"t: {t}, PV: {PV}, u: {u}\")\n", + "\n", + "\n", + " plant.step()\n", + " print(f\"t: {t}, PV: {plant.get_sensor_value()}, u: {plant.get_throttle_value()}\")\n", + " rows.append((t, plant.get_sensor_value(), SP, plant.get_throttle_value()))\n", + " t += dt\n", + " # time.sleep(dt)\n", + "\n", + " if realtime:\n", + " target = start_wall + t\n", + " now = time.perf_counter()\n", + " print(f\"target: {target}, now: {now}\")\n", + " if target > now:\n", + " print(f\"sleeping for {target - now}\")\n", + " time.sleep(target - now)\n", + "\n", + " df = pd.DataFrame(rows, columns=[\"time_s\", \"PV\", \"SP\", \"throttle\"])\n", + "\n", + " if csv_path:\n", + " Path(csv_path).parent.mkdir(parents=True, exist_ok=True)\n", + " df.to_csv(csv_path, index=False)\n", + "\n", + " return df\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "f9a08836", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "t: 0.0, PV: 40.0, u: 0.0\n", + "t: 0.0, PV: 40.0, u: 0.0\n", + "target: 9779670.124661956, now: 9779670.124898069\n", + "t: 0.0, PV: 40.0, u: 0.0\n", + "target: 9779670.124661956, now: 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9779670.124661956, now: 9779678.122691376\n", + "t: 0.0, PV: 39.98727691972615, u: 0.0\n", + "target: 9779670.124661956, now: 9779678.122759411\n", + "t: 0.0, PV: 39.98579886089139, u: 0.0\n", + "target: 9779670.124661956, now: 9779678.122823508\n", + "t: 0.0, PV: 39.98446269514434, u: 0.0\n", + "target: 9779670.124661956, now: 9779678.12288553\n", + "t: 0.0, PV: 39.983281773011456, u: 0.0\n", + "target: 9779670.124661956, now: 9779678.12294702\n", + "t: 0.0, PV: 39.98226789387633, u: 0.0\n" + ] + }, + { + "ename": "KeyboardInterrupt", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[6], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;66;03m# Run with YAML-equivalent defaults\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m df \u001b[38;5;241m=\u001b[39m \u001b[43mrun_sim\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3\u001b[0m \u001b[38;5;28mprint\u001b[39m(df)\n", + "Cell \u001b[0;32mIn[5], line 69\u001b[0m, in \u001b[0;36mrun_sim\u001b[0;34m(duration_s, controller_period_s, T0, C, R_th, T_env, throttle_mode, I_max, R_heater, eta, P_max, dt, SP, Kp, Ki, Kd, I_min, du_min, derivative_smoothing, int_limit, enable_offset_term, u_offset_baseline, csv_path, realtime)\u001b[0m\n\u001b[1;32m 65\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mt: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mt\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m, PV: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mPV\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m, u: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mu\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 68\u001b[0m plant\u001b[38;5;241m.\u001b[39mstep()\n\u001b[0;32m---> 69\u001b[0m \u001b[38;5;28;43mprint\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mt: \u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mt\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m, PV: \u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mplant\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_sensor_value\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m, u: \u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mplant\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_throttle_value\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 70\u001b[0m rows\u001b[38;5;241m.\u001b[39mappend((t, plant\u001b[38;5;241m.\u001b[39mget_sensor_value(), SP, plant\u001b[38;5;241m.\u001b[39mget_throttle_value()))\n\u001b[1;32m 71\u001b[0m \u001b[38;5;66;03m# t += dt\u001b[39;00m\n\u001b[1;32m 72\u001b[0m \u001b[38;5;66;03m# time.sleep(dt)\u001b[39;00m\n", + "File \u001b[0;32m~/yao-cca-controls/.venv/lib/python3.10/site-packages/ipykernel/iostream.py:684\u001b[0m, in \u001b[0;36mOutStream.write\u001b[0;34m(self, string)\u001b[0m\n\u001b[1;32m 682\u001b[0m \u001b[38;5;66;03m# only touch the buffer in the IO thread to avoid races\u001b[39;00m\n\u001b[1;32m 683\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_buffer_lock:\n\u001b[0;32m--> 684\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_buffers\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;28;43mfrozenset\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mparent\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mitems\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstring\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 685\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_child:\n\u001b[1;32m 686\u001b[0m \u001b[38;5;66;03m# mp.Pool cannot be trusted to flush promptly (or ever),\u001b[39;00m\n\u001b[1;32m 687\u001b[0m \u001b[38;5;66;03m# and this helps.\u001b[39;00m\n\u001b[1;32m 688\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_subprocess_flush_pending:\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: " + ] + } + ], + "source": [ + "\n", + "# Run with YAML-equivalent defaults\n", + "df = run_sim()\n", + "print(df)\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "8157edbb", + "metadata": {}, + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8a564852", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "# PV vs SP\n", + "plt.figure()\n", + "plt.plot(df[\"time_s\"], df[\"PV\"], label=\"PV (sensor)\")\n", + "plt.plot(df[\"time_s\"], df[\"SP\"], linestyle=\"--\", label=\"SP (setpoint)\")\n", + "plt.xlabel(\"Time [s]\")\n", + "plt.ylabel(\"Temperature [K]\")\n", + "plt.title(\"PID: Sensor vs Setpoint — YAML-accurate\")\n", + "plt.legend(); plt.grid(True); plt.show()\n", + "\n", + "# Throttle\n", + "plt.figure()\n", + "plt.plot(df[\"time_s\"], df[\"throttle\"], label=\"Throttle (A)\")\n", + "plt.xlabel(\"Time [s]\")\n", + "plt.ylabel(\"Throttle\")\n", + "plt.title(\"PID: Actuator Command — YAML-accurate\")\n", + "plt.legend(); plt.grid(True); plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3285793b", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8fe251f0", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d7916bcb", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/dripline/extensions/pid_loop/__init__.py b/dripline/extensions/pid_loop/__init__.py new file mode 100644 index 0000000..412bde7 --- /dev/null +++ b/dripline/extensions/pid_loop/__init__.py @@ -0,0 +1,5 @@ +__all__ = [] + +# Modules in this directory +from .pid_loop_v2 import * + diff --git a/dripline/extensions/pid_loop/logs/logs/pid_log_2025-10-07T06:59:08.867854.csv b/dripline/extensions/pid_loop/logs/logs/pid_log_2025-10-07T06:59:08.867854.csv new file mode 100644 index 0000000..9575586 --- /dev/null +++ b/dripline/extensions/pid_loop/logs/logs/pid_log_2025-10-07T06:59:08.867854.csv @@ -0,0 +1,250 @@ +2025-10-07T06:59:09.926670,0.75,85.0,2.5 +2025-10-07T06:59:10.966138,0.75,85.0,2.5 +2025-10-07T06:59:11.980553,0.75,85.0,2.5 +2025-10-07T06:59:12.984025,0.75,85.0,2.5 +2025-10-07T06:59:14.000184,0.75,85.0,2.5 +2025-10-07T06:59:15.034925,0.75,85.0,2.5 +2025-10-07T06:59:16.070448,0.75,85.0,2.5 +2025-10-07T06:59:17.110117,0.75,85.0,2.5 +2025-10-07T06:59:18.134831,0.75,85.0,2.5 +2025-10-07T06:59:19.146179,0.75,85.0,2.5 +2025-10-07T06:59:20.164908,0.75,85.0,2.5 +2025-10-07T06:59:21.194494,0.75,85.0,2.5 +2025-10-07T06:59:22.225395,0.75,85.0,2.5 +2025-10-07T06:59:23.260403,0.75,85.0,2.5 +2025-10-07T06:59:24.285556,0.75,85.0,2.5 +2025-10-07T06:59:25.331096,0.75,85.0,2.5 +2025-10-07T06:59:26.366090,0.75,85.0,2.5 +2025-10-07T06:59:27.374252,0.75,85.0,2.5 +2025-10-07T06:59:28.420414,0.75,85.0,2.5 +2025-10-07T06:59:29.422576,0.75,85.0,2.5 +2025-10-07T06:59:30.438536,0.75,85.0,2.5 +2025-10-07T06:59:31.464295,0.75,85.0,2.5 +2025-10-07T06:59:32.497876,0.75,85.0,2.5 +2025-10-07T06:59:33.512986,0.75,85.0,2.5 +2025-10-07T06:59:34.535882,0.75,85.0,2.5 +2025-10-07T06:59:35.575783,0.75,85.0,2.5 +2025-10-07T06:59:36.622185,0.75,85.0,2.5 +2025-10-07T06:59:37.633709,0.75,85.0,2.5 +2025-10-07T06:59:38.666155,0.75,85.0,2.5 +2025-10-07T06:59:39.689665,0.75,85.0,2.5 +2025-10-07T06:59:40.716399,0.75,85.0,2.5 +2025-10-07T06:59:41.756927,0.75,85.0,2.5 +2025-10-07T06:59:42.792790,0.75,85.0,2.5 +2025-10-07T06:59:43.830068,0.75,85.0,2.5 +2025-10-07T06:59:44.843962,0.75,85.0,2.5 +2025-10-07T06:59:45.891759,0.75,85.0,2.5 +2025-10-07T06:59:46.919160,0.75,85.0,2.5 +2025-10-07T06:59:47.921950,0.75,85.0,2.5 +2025-10-07T06:59:48.947950,0.75,85.0,2.5 +2025-10-07T06:59:49.979779,0.75,85.0,2.5 +2025-10-07T06:59:51.000594,0.75,85.0,2.5 +2025-10-07T06:59:52.052465,0.75,85.0,2.5 +2025-10-07T06:59:53.084528,0.75,85.0,2.5 +2025-10-07T06:59:54.090876,0.75,85.0,2.5 +2025-10-07T06:59:55.126672,0.75,85.0,2.5 +2025-10-07T06:59:56.149151,0.75,85.0,2.5 +2025-10-07T06:59:57.179252,0.75,85.0,2.5 +2025-10-07T06:59:58.223441,0.75,85.0,2.5 +2025-10-07T06:59:59.258723,0.75,85.0,2.5 +2025-10-07T07:00:00.280775,0.75,85.0,2.5 +2025-10-07T07:00:01.311827,0.75,85.0,2.5 +2025-10-07T07:00:02.322223,0.75,85.0,2.5 +2025-10-07T07:00:03.335563,0.75,85.0,2.5 +2025-10-07T07:00:04.339653,0.75,85.0,2.5 +2025-10-07T07:00:05.384961,0.75,85.0,2.5 +2025-10-07T07:00:06.417769,0.75,85.0,2.5 +2025-10-07T07:00:07.439965,0.75,85.0,2.5 +2025-10-07T07:00:08.481933,0.75,85.0,2.5 +2025-10-07T07:00:09.530889,0.75,85.0,2.5 +2025-10-07T07:00:10.567536,0.75,85.0,2.5 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z>s3q@t>euzN_FT6`ZNyGPZE-{cH=_0e*pVbJkL3hp^nn*{=&M{y(fs+|24lh@ln+EPStP?+fQaJ`lxiG*;go-Y(Y|jzZ6*n{nzm{G5e7{Dab9 zK=|>+Z3!qFV$^n>`1Gw$qbJ`7_w9QQ@3^bki&rLqPcoi)&@a&$&=E|q^;`Olq~u}8 zO*q=|D9$oartkW7OpchJu>n-=`rCm0q%I5g>8jbn#eBL9IWGFdj7=qjFJAL!8Z<=z zd?^QOfKRRu0zB#m)BKg0)XPY%DO?#NoXR7+zN@FY!{$4@M{oF`l&I^qj~R$;?< zYd-VP9_y^2Dw5Jn=~gt9iI@Rl*}9_uofxxg_41&)CG8x9k6^F{SqUU zz(Z2Hm(S4OMMTCaxqY2k_Ezvn6sdwTE*Tv#S$c^8Cdn4kp>+Ib(hsM?aw@PR(^pHk z{;vnC@H5d*{{5)%zxuzgZ$=9T-|2jXUv722a6q%*#f;Tch2za1{5m=PHCp_E;N6LQ zGeu|%x7s4OFCrrPGpq#P^qV<3l3H=ud)~2a_twlUR;T|P D3@6r+ literal 0 HcmV?d00001 diff --git a/dripline/extensions/pid_loop/logs/plot.py b/dripline/extensions/pid_loop/logs/plot.py new file mode 100644 index 0000000..a7d1903 --- /dev/null +++ b/dripline/extensions/pid_loop/logs/plot.py @@ -0,0 +1,62 @@ +import csv +import glob +import os +from datetime import datetime +import matplotlib.pyplot as plt + +log_dir = "./logs" +csv_files = glob.glob(os.path.join(log_dir, "pid_log*.csv")) +print(f"Found {len(csv_files)} CSV files in {log_dir}") +print(f"CSV files: {csv_files}") + +for csv_file in csv_files: + times, PV, SP, throttle = [], [], [], [] + + with open(csv_file, "r") as f: + reader = csv.reader(f) + for row in reader: + # assuming column order: time, PV, SP, throttle + try: + times.append(datetime.fromisoformat(row[0])) + PV.append(float(row[1])) + SP.append(float(row[2])) + throttle.append(float(row[3])) + except Exception as e: + print(f"Skipping row in {csv_file}: {row}, error={e}") + + if not times: + print(f"Skipping {csv_file}, no valid data") + continue + + # Use filename (without extension) as title + title_str = os.path.basename(csv_file).replace(".csv", "") + print(f"Saving plot to {title_str}_sensor.png") + print(f"Saving plot to {title_str}_throttle.png") + + # Sensor vs Setpoint + plt.figure() + plt.plot(times, PV, 'ro', label="PV (sensor)", ms=1) + plt.plot(times, SP, label="SP (setpoint)", linestyle="--") + plt.xlabel("Time") + plt.ylabel("Sensor Value") + plt.title(f"{title_str}: Sensor vs Setpoint") + plt.legend() + plt.grid(True) + plt.savefig(f"{title_str}_sensor.png", dpi=300) + plt.close() + + # Throttle vs Time + plt.figure() + plt.plot(times, throttle, 'go', label="Throttle (actuator)", ms=1) + plt.xlabel("Time") + plt.ylabel("Throttle") + plt.title(f"{title_str}: Throttle") + plt.legend() + plt.grid(True) + plt.savefig(f"{title_str}_throttle.png", dpi=300) + plt.close() + print(f"Saved plot to {title_str}_throttle.png") + print(f"Saved plot to {title_str}_sensor.png") + print(f"Saved plot to {title_str}_throttle.png") + +print("Plots saved for all CSV files in logs/") diff --git a/dripline/extensions/pid_loop/pid_loop.py b/dripline/extensions/pid_loop/pid_loop.py new file mode 100644 index 0000000..251b6fd --- /dev/null +++ b/dripline/extensions/pid_loop/pid_loop.py @@ -0,0 +1,200 @@ +''' +Implementation of a PID control loop +''' + +from __future__ import print_function +__all__ = [] + +import time +import datetime +import dripline +from dripline.core import Service, ThrowReply +print("Dripline location:", dripline.__file__) # Debugging line to check the location of Dripline +print("Dripline Version:", dripline.__version__) # Debugging line to check the version of Dripline +print(f"Service methods: {dir(Service)}") # Check if 'get' is listed +import logging +logger = logging.getLogger(__name__) + +__all__.append('PidController') +class PidController(Service): + ''' + Implementation of a PID control loop with constant offset. That is, the PID equation + is used to compute the **change** to the value of some channel and not the value + itself. In the case of temperature control, this makes sense if the loop is working + against some fixed load (such as a cryocooler). + + The input sensor can be anything which broadcasts regular values on the alerts + exchange (using the standard sensor_value. routing key format). Usually + this would be a temperature sensor, but it could be anything. Similarly, the + output is anything that can be set to a float value, though a current output + is probably most common. After setting the new value of current, this value is checked + to be within a range around the desired value. + + **NOTE** + The "exchange" and "keys" arguments list below come from the Service class but + are not valid for this class. Any value provided will be ignored + ''' + + def __init__(self, + input_channel, + output_channel, + check_channel, + status_channel, + payload_field='value_cal', + tolerance = 0.01, + target_value=110, + proportional=0.0, integral=0.0, differential=0.0, + maximum_out=1.0, minimum_out=1.0, delta_out_min= 0.001, + enable_offset_term=True, + minimum_elapsed_time=0, + **kwargs + ): + ''' + input_channel (str): name of the logging sensor to use as input to PID (this will override any provided values for keys) + output_channel (str): name of the endpoint to be set() based on PID + check_channel (str): name of the endpoint to be checked() after a set() + status_channel (str): name of the endpoint which controls the status of the heater (enabled/disabled output) + payload_field (str): name of the field in the payload when the sensor logs (default is 'value_cal' and 'value_raw' is the only other expected value) + target_value (float): numerical value to which the loop will try to lock the input_channel + proportional (float): coefficient for the P term in the PID equation + integral (float): coefficient for the I term in the PID equation + differential (float): coefficient for the D term in the PID equation + maximum_out (float): max value to which the output_channel may be set; if the PID equation gives a larger value this value is used instead + delta_out_min (float): minimum value by which to change the output_channel; if the PID equation gives a smaller change, the value is left unchanged (no set is attempted) + tolerance (float): acceptable difference between the set and get values (default: 0.01) + minimum_elapsed_time (float): minimum time interval to perform PID calculation over + ''' + kwargs.update({'keys':['sensor_value.'+input_channel]}) + Service.__init__(self, **kwargs) + + self._set_channel = output_channel + self._check_channel = check_channel + self._status_channel = status_channel + self.payload_field = payload_field + self.tolerance = tolerance + + self._last_data = {'value':None, 'time':datetime.datetime.now(datetime.UTC)} + self.target_value = target_value + + self.Kproportional = proportional + self.Kintegral = integral + self.Kdifferential = differential + + self._integral= 0 + + self.max_current = maximum_out + self.min_current = minimum_out + self.min_current_change = delta_out_min + + self.enable_offset_term = enable_offset_term + self.minimum_elapsed_time = minimum_elapsed_time + + self._force_reprocess = False + + self.__validate_status() + self._old_current = self.__get_current() + logger.info(f'starting current is: {self._old_current}') + + def __get_current(self): + value = self.get(self._check_channel)[self.payload_field] + logger.info(f'current get is {value}') + + try: + value = float(value) + except (TypeError, ValueError): + ThrowReply('service_error_invalid_value', f'value get ({value}) is not floatable') + return value + + def __validate_status(self): + value = self.get(self._status_channel)[self.payload_field] + if value == 'enabled': + logger.debug(f"{self._status_channel} returns {value}") + else: + logger.critical(f"Invalid status of {self._status_channel} for PID control by {self.name}") + ThrowReply('resource_error', f"{self._status_channel} returns {value}") + + def this_consume(self, message, method): + logger.info('consuming message') + this_value = message.payload[self.payload_field] + if this_value is None: + logger.info('value is None') + return + + this_time = datetime.datetime.strptime(message['timestamp'], '%d/%m/%y %H:%M:%S.%f') + if (this_time - self._last_data['time']).total_seconds() < self.minimum_elapsed_time: + # handle self._force_reprocess from @target_value.setter + if not self._force_reprocess: + logger.info(f"not enough time has elasped: {(this_time - self._last_data['time']).total_seconds()}[{self.minimum_elapsed_time}]") + return + logger.info("Forcing process due to changed target_value") + self._force_reprocess = False + + self.process_new_value(timestamp=this_time, value=float(this_value)) + + @property + def target_value(self): + return self._target_value + @target_value.setter + def target_value(self, value): + self._target_value = value + self._integral = 0 + self._force_reprocess = True + + def set_current(self, value): + logger.info(f'going to set new current to: {value}') + reply = self.set(self._set_channel, value) + logger.info(f'set response was: {reply}') + + def process_new_value(self, value, timestamp): + + delta = self.target_value - value + logger.info(f'value is <{value}>; delta is <{delta}>') + + self._integral += delta * (timestamp - self._last_data['time']).total_seconds() + if (timestamp - self._last_data['time']).total_seconds() < 2*self.minimum_elapsed_time: + try: + derivative = (self._last_data['value'] - value) / (timestamp - self._last_data['time']).total_seconds() + except TypeError: + derivative = 0 + else: + logger.warning("invalid time for calculating derivative") + derivative = 0. + self._last_data = {'value': value, 'time': timestamp} + + logger.info(f"""proportional <{self.Kproportional * delta}>; \ + integral <{self.Kintegral * self._integral}>; \ + differential <{self.Kdifferential * derivative}>""") + change_to_current = (self.Kproportional * delta + + self.Kintegral * self._integral + + self.Kdifferential * derivative + ) + new_current = (self._old_current or 0)*self.enable_offset_term + change_to_current + + if abs(change_to_current) < self.min_current_change: + logger.info("current change less than min delta") + logger.info(f"old[new] are: {self._old_current}[{new_current}]") + return + logger.info(f'computed new current to be: {new_current}') + if new_current > self.max_current: + logger.info("new current above max") + new_current = self.max_current + if new_current < self.min_current: + logger.info("new current below min") + new_current = self.min_current + if new_current < 0.: + logger.info("new current < 0") + new_current = 0. + + self.set_current(new_current) + logger.debug("allow settling time and checking the current value") + # FIXME: remove sleep when set_and_check handled properly + time.sleep(1) + current_get = self.__get_current() + if abs(current_get-new_current) < self.tolerance: + logger.debug("current set is equal to current get") + else: + self.__validate_status() + ThrowReply(f'service_error_invalid_value', "set value ({new_current}) is not equal to checked value ({current_get})") + + logger.info(f"current set is: {new_current}") + self._old_current = new_current diff --git a/dripline/extensions/pid_loop/pid_loop_v2.py b/dripline/extensions/pid_loop/pid_loop_v2.py new file mode 100644 index 0000000..75f6b8f --- /dev/null +++ b/dripline/extensions/pid_loop/pid_loop_v2.py @@ -0,0 +1,552 @@ +""" +Author: yao + +PID controller for a heater driving a cryogenic/vacuum system. + +This version preserves the original public interface: +- Methods: __get_current, __validate_status, this_consume, process_new_value, set_current +- Property: target_value (getter/setter) + +Enhancements (backwards-compatible) +----------------------------------- +- Anti-windup: integral clamping + back-calculation when output saturates +- Bounded "set & verify" loop instead of fixed sleep +- Derivative-on-measurement with optional EMA smoothing (reduces setpoint kick) +- Safer time handling (guards against dt<=0 and timestamp parse issues) +- Output deadband to avoid chatter +- Sane default for minimum_out (=0.0 instead of 1.0) + +Conventions / Units +------------------- +- PV (process variable): e.g., temperature in Kelvin +- SP (setpoint): same units as PV +- Output u: actuator command (e.g., current in A or duty [0..1]) +- Time: seconds +""" + +from __future__ import annotations + +import time +import datetime +import logging +from typing import Optional +import threading + +import csv +import atexit +from typing import Optional, Any, Tuple +import queue +from dripline.core import Service, ThrowReply + +logger = logging.getLogger(__name__) +logger.setLevel(logging.INFO) + + +def clamp(x: float, lo: float, hi: float) -> float: + """Clamp x to the inclusive range [lo, hi].""" + return lo if x < lo else hi if x > hi else x + + +class PidController(Service): + """ + PID control loop Service (positional PID form with optional baseline offset). + + Control law (positional PID): + e = SP - PV + u = u_offset + Kp*e + Ki*integral(e) dt - Kd * d(PV)/dt + (minus sign on derivative since d(e)/dt = -d(PV)/dt) + + Public API preserved from original: + - this_consume(message, method) + - process_new_value(value, timestamp) + - set_current(value) + - target_value property + - __get_current(), __validate_status() + """ + + def __init__(self, + input_channel: str, + output_channel: str, + check_channel: str, + status_channel: str, + payload_field: str = 'value_cal', + tolerance: float = 0.01, + target_value: float = 85.0, + proportional: float = 0.0, + integral: float = 0.0, + differential: float = 0.0, + maximum_out: float = 1.0, + minimum_out: float = 0.0, # CHANGED default from 1.0 -> 0.0 (sane) + delta_out_min: float = 0.001, # Minimum current change + enable_offset_term: bool = False, # Use old current as baseline + minimum_elapsed_time: float = 0.0, + poll_period_s: float = 0.1, # NEW: polling period for input_channel + # --- New, optional, backward-compatible knobs below --- + integral_limit: Optional[float] = None, # |integral(e) dt| cap for anti-windup + derivative_smoothing: float = 0.0, # EMA factor in [0,1]; 0 = off + max_settle_wait_s: float = 3.0, # bounded verify-after-set + u_offset_baseline: float = 0.0, # explicit baseline if offset term desired + **kwargs): + """ + Initialize the PID controller and runtime state. + + Most arguments mirror the original class. New optional arguments are kept + at the end and have safe defaults (won't change behavior unless used). + """ + + # DO NOT try to pass 'keys' here; it will be ignored by Service + # kwargs.update({'keys': [f'sensor_value.{input_channel}']}) # <-- remove this + super().__init__(**kwargs) + + + # Channels & config + self._input_channel = input_channel + self._poll_period_s = float(poll_period_s) + self._set_channel = output_channel + self._check_channel = check_channel + self._status_channel = status_channel + self.payload_field = payload_field + self.tolerance = float(tolerance) + + # Controller gains and setpoint + self._target_value = float(target_value) + self.Kproportional = float(proportional) + self.Kintegral = float(integral) + self.Kdifferential = float(differential) + + # Output limits / shaping (names kept) + self.max_current = float(maximum_out) + self.min_current = float(minimum_out) + self.min_current_change = float(delta_out_min) + + + # Original flag retained; now combined with an explicit baseline + self.enable_offset_term = bool(enable_offset_term) + self.u_offset_baseline = float(u_offset_baseline) + self.max_settle_wait_s = float(max_settle_wait_s) + + # Timing & stability + self.minimum_elapsed_time = max(0.0, float(minimum_elapsed_time)) + + # Anti-windup & derivative smoothing + self._integral = 0.0 + self._int_limit = None if integral_limit is None else abs(float(integral_limit)) + self._alpha_d = clamp(float(derivative_smoothing), 0.0, 1.0) + self._ema_dpvdt = 0.0 + self._last_data = {'value': None, 'time': None} # timestamp will be datetime or None + + # Forcing reprocess on SP change (as in the original) + self._force_reprocess = False + + # Verify device state and seed last output + self.__validate_status() + self._old_current = self.__get_current() + logger.info(f"PID ready: start_u={self._old_current}, SP={self._target_value}, " + f"Kp={self.Kproportional}, Ki={self.Kintegral}, Kd={self.Kdifferential}") + + + # --- simple CSV logging state --- + self._log_data = [] # buffer: list of (time_iso, PV, SP, throttle) + self._log_lock = threading.Lock() + self._log_filename = f"/app/logs/pid_log_{datetime.datetime.now().isoformat()}.csv" + self._log_autoflush_every = 10 # autosave every N rows + self._log_file_initialized = False # write header once on first flush + + + # NEW: storage for logging data + self._log_data = [] # list of (timestamp, PV, SP, throttle) + + # Register save-on-exit + # atexit.register(self._save_log_to_csv) + + # start polling thread + t = threading.Thread(target=self._poll_sensor_loop, name="pid-poll", daemon=True) + t.start() + + # New: poller that incorporates all logic from this_consume() + def _poll_sensor_loop(self) -> None: + """ + Periodically GET the PV endpoint and run the same logic formerly in this_consume(). + """ + while True: + try: + # 1) GET PV from the input endpoint + # resp = self.get(self._input_channel) + resp = self._get_with_deadline(self._input_channel, timeout_s=max(1.0, 0.8*self._poll_period_s + 0.2)) + if not resp: + # No data this tick; keep cadence and try again + time.sleep(self._poll_period_s) + continue + # Extract PV + this_value = resp.get(self.payload_field) + logger.info(f"Message payload value: {this_value}") + if this_value is None: + logger.info('value is None') + time.sleep(self._poll_period_s) + continue + + # 2) Parse timestamp robustly (keep your original format first) + ts_raw = None + # Try common places a timestamp might live + if hasattr(resp, 'get'): + ts_raw = resp.get('timestamp') or resp.get('time') or resp.get('ts') + this_time = None + if ts_raw: + try: + this_time = datetime.datetime.strptime(ts_raw, '%d/%m/%y %H:%M:%S.%f') + except Exception: + logger.debug(f"timestamp parse failed for '{ts_raw}', using utcnow()") + if this_time is None: + this_time = datetime.datetime.utcnow() + logger.info(f"This time: {this_time}") + + logger.info(f"[PID READ] PV={float(this_value)} at {this_time.isoformat()}") + + + + # 3) Enforce minimum interval unless forced by SP change + last_time = self._last_data['time'] + if last_time is not None: + dt = (this_time - last_time).total_seconds() + if dt < self.minimum_elapsed_time and not self._force_reprocess: + logger.info(f"not enough time has elapsed: {dt:.3f}s " + f"[min {self.minimum_elapsed_time:.3f}s]") + time.sleep(self._poll_period_s) + continue + if self._force_reprocess: + logger.info("Forcing process due to changed target_value") + self._force_reprocess = False + + # 4) Dispatch to the PID step + try: + self.process_new_value(value=float(this_value), timestamp=this_time) + except (TypeError, ValueError): + logger.info(f"value not floatable: {this_value}") + + except Exception as ex: + logger.exception(f"[PV poll] failure: {ex}") + + # TODO IS THIS NECESSARY? + # # cadence for polling + # time.sleep(self._poll_period_s) + + def _log_append(self, timestamp: datetime.datetime, pv: float, sp: float, u: float) -> None: + row = (timestamp.isoformat(), float(pv), float(sp), float(u) if u is not None else float("nan")) + need_flush = False + with self._log_lock: + self._log_data.append(row) + if len(self._log_data) >= self._log_autoflush_every: + need_flush = True + if need_flush: + self._flush_log_to_csv() + + # def save_log(self, filename: Optional[str] = None) -> None: + # """ + # Public method: force a flush of the in-memory log buffer to CSV. + # If 'filename' is provided, switch output file and reset header handling. + # """ + # if filename: + # with self._log_lock: + # # If the filename changes, re-initialize header for the new file + # if filename != self._log_filename: + # self._log_filename = filename + # self._log_file_initialized = False + # self._flush_log_to_csv() + + def _flush_log_to_csv(self) -> None: + """ + Flush the buffered rows to CSV (append mode). Writes header once per file. + Clears the buffer after writing. + """ + rows = None + with self._log_lock: + if not self._log_data: + return + rows = self._log_data + self._log_data = [] + + mode = "a" + try: + with open(self._log_filename, mode, newline="") as f: + writer = csv.writer(f) + # if not self._log_file_initialized: + # writer.writerow(["time", "PV", "SP", "throttle"]) + # self._log_file_initialized = True + writer.writerows(rows) + logger.info(f"Appended {len(rows)} rows to {self._log_filename}") + except Exception as ex: + logger.exception(f"Failed flushing CSV: {ex}") + + # ------------------------------------------------------------------ # + # Public API: helper methods preserved from original implementation + # ------------------------------------------------------------------ # + + def __get_current(self) -> float: + """ + Read and return the actuator value from check_channel. + + Returns + ------- + float : Current actuator reading (same units as output u). + """ + # value = self.get(self._check_channel)[self.payload_field] + resp = self._get_with_deadline(self._check_channel, timeout_s=1.0) + if not resp: + raise ThrowReply('service_error_invalid_value', 'current read timeout/no reply') + value = resp.get(self.payload_field) + try: + value = float(value) + except (TypeError, ValueError): + raise ThrowReply('service_error_invalid_value', f'value get ({value}) is not floatable') + logger.info(f'current get is {value}') + return value + + def __validate_status(self) -> None: + """ + Ensure the status_channel reports 'enabled'; otherwise raise ThrowReply. + """ + # value = str(self.get(self._status_channel)[self.payload_field]).strip().lower() + value = self.get(self._status_channel)[self.payload_field] + if value: + logger.debug(f"{self._status_channel} returns {value}") + else: + logger.critical(f"Invalid status of {self._status_channel} for PID control by {self.name}") + raise ThrowReply('resource_error', f"{self._status_channel} returns {value}") + + @property + def target_value(self) -> float: + """ + Get the current setpoint (SP). + """ + return self._target_value + + @target_value.setter + def target_value(self, value: float) -> None: + """ + Set the setpoint (SP) and reset integral; force next process step. + + Notes + ----- + Resetting the integral prevents previous bias from the old SP. + """ + logger.info(f"setting new target_value to: {value}") + logger.info(f"old target_value was: {self._target_value}") + logger.info("Resetting integral to 0.0") + logger.info("Forcing reprocess on next message") + self._target_value = float(value) + self._integral = 0.0 + self._force_reprocess = True + + def set_current(self, value: float) -> None: + """ + Send command to the actuator via set_channel and log the reply. + """ + logger.info(f'going to set new current to: {value}') + ok, reply = self._set_with_deadline(self._set_channel, value, timeout_s=1.0) + if not ok: + logger.warning("set_current: no reply (timeout/failure)") + logger.info(f'set response was: {reply}') + + # ------------------------------------------------------------------ # + # Public API: step function with original name/signature preserved + # ------------------------------------------------------------------ # + # ---- Deadline-bounded wrappers around blocking self.get/self.set ---- + def _get_with_deadline(self, channel: str, timeout_s: float = 1.0) -> Optional[dict]: + """ + Run self.get(channel) in a worker thread and return within timeout_s. + Returns the payload dict on success, or None on timeout/error. + """ + q: "queue.Queue[Tuple[bool, Any]]" = queue.Queue(maxsize=1) + + def _worker(): + try: + resp = self.get(channel) + q.put((True, resp)) + except Exception as ex: + q.put((False, ex)) + + t = threading.Thread(target=_worker, name=f"get:{channel}", daemon=True) + t.start() + try: + ok, val = q.get(timeout=timeout_s) + if ok: + return val # type: ignore[return-value] + logger.warning(f"GET {channel} failed: {val}") + return None + except queue.Empty: + logger.warning(f"GET {channel} timed out after {timeout_s:.2f}s") + return None + finally: + t.join(timeout=0.1) # Clean up the thread + + def _set_with_deadline(self, channel: str, value: float, timeout_s: float = 1.0) -> Tuple[bool, Any]: + """ + Run self.set(channel, value) with a deadline. + Returns (ok, reply_or_exception). When ok is False, reply_or_exception is the exception or None on timeout. + """ + q: "queue.Queue[Tuple[bool, Any]]" = queue.Queue(maxsize=1) + + def _worker(): + try: + reply = self.set(channel, value) + q.put((True, reply)) + except Exception as ex: + q.put((False, ex)) + + t = threading.Thread(target=_worker, name=f"set:{channel}", daemon=True) + t.start() + try: + ok, val = q.get(timeout=timeout_s) + if ok: + logger.debug(f"SET {channel} reply: {val}") + return True, val + logger.warning(f"SET {channel} failed: {val}") + return False, val + except queue.Empty: + logger.warning(f"SET {channel} timed out after {timeout_s:.2f}s") + return False, None + finally: + t.join(timeout=0.1) # Clean up the thread + + def process_new_value(self, value: float, timestamp: datetime.datetime) -> None: + """ + Execute one PID update given a new measurement. + + Parameters + ---------- + value : float + Latest PV (e.g., temperature). + timestamp : datetime.datetime + Timestamp associated with the measurement (any tz/naive ok). + + Steps + ----- + 1) Compute dt safely and gate on minimum_elapsed_time. + 2) Compute error e = SP - PV. + 3) Update integral (with optional clamping). + 4) Derivative on measurement with optional EMA smoothing. + 5) Positional PID output with optional offset term. + 6) Saturate and apply anti-windup back-calculation. + 7) Apply output deadband; otherwise set & verify (bounded wait). + """ + # --- 1) Compute dt and update last_data timestamp/value + last_time = self._last_data['time'] + last_value = self._last_data['value'] + + if last_time is None: + # First call: initialize and return (need two samples for derivative) + self._last_data = {'value': value, 'time': timestamp} + logger.debug("initialized last_data on first sample") + return + + dt = (timestamp - last_time).total_seconds() + if dt <= 0: + # Guard against clock anomalies; use a tiny positive dt + dt = max(self.minimum_elapsed_time, 1e-6) + + if dt < self.minimum_elapsed_time: + # Redundant—already gated in this_consume, but keep for safety + logger.debug(f"skip: dt {dt:.6f} < min {self.minimum_elapsed_time:.6f}") + return + + # --- 2) Error + error = self._target_value - value + logger.info(f"target value = {self._target_value:.3f}, sensor value = {value:.3f}") + logger.info(f"Current error is: {error:.3f}") + + # --- 3) Integral with optional clamping + self._integral += error * dt + # if self._int_limit is not None: + # self._integral = clamp(self._integral, -self._int_limit, self._int_limit) + + # --- 4) Derivative on measurement (reduces setpoint kick) + if last_value is None: + d_pv_dt = 0.0 + else: + raw_d = (value - last_value) / dt + # Optional EMA smoothing + # self._ema_dpvdt = (self._alpha_d * self._ema_dpvdt + # + (1.0 - self._alpha_d) * raw_d) + # d_pv_dt = self._ema_dpvdt + d_pv_dt = raw_d # uncomment to disable smoothing + + # --- Update last sample after derivative calc + self._last_data = {'value': value, 'time': timestamp} + + # --- 5) Positional PID output (keep original naming for gains) + # Baseline offset behavior kept: if enable_offset_term, include baseline + # composed of last commanded value and/or explicit u_offset_baseline. + baseline = (self._old_current if self.enable_offset_term else 0.0) + self.u_offset_baseline + change_terms = (self.Kproportional * error + + self.Kintegral * self._integral + - self.Kdifferential * d_pv_dt) + new_current = baseline + change_terms + logger.info(f"Baseline={baseline:.3f}, delta_terms={change_terms:.3f}") + logger.info(f"Raw new current (pre-sat) = {new_current:.3f}") + + # --- 6) Saturation + anti-windup back-calculation + new_current_sat = clamp(new_current, self.min_current, self.max_current) + if new_current != new_current_sat and self.Kintegral > 0.0: + # Back-calc: adjust integral to make effective output equal the sat value + self._integral += (new_current_sat - new_current) / self.Kintegral + if self._int_limit is not None: + self._integral = clamp(self._integral, -self._int_limit, self._int_limit) + new_current = new_current_sat + else: + new_current = new_current_sat + logger.info(f"Saturation adjusted new current = {new_current:.3f}") + + # --- 7) Output deadband; set & verify + if abs(new_current - (self._old_current or 0.0)) < self.min_current_change: + logger.info("current change less than min delta") + logger.info(f"old[new] are: {self._old_current:.3f}[{new_current:.3f}]") + # Log even if we didn't update current + self._log_append(timestamp, value, self._target_value, self._old_current) + return + + self.set_current(new_current) + # self._verify_after_set(new_current) + + # NEW: append log row + self._log_append(timestamp, value, self._target_value, new_current) + + logger.info(f"PV={value:.4f} SP={self._target_value:.4f} e={error:.4f} dt={dt:.3f} " + f"u={new_current:.6f} (Kp={self.Kproportional}, Ki={self.Kintegral}, Kd={self.Kdifferential})") + + self._old_current = new_current + + # ------------------------------------------------------------------ # + # Private helpers (new, but do not change public surface) + # ------------------------------------------------------------------ # + + # def _verify_after_set(self, u_cmd: float) -> None: + # """ + # Poll check_channel up to max_settle_wait_s until |read - set| <= tolerance. + + # Raises + # ------ + # ThrowReply + # If actuator does not report the commanded value within the tolerance + # before timeout. Revalidates status before raising. + # """ + # t0 = time.monotonic() + # last_exc = None + # u_read = None + # while (time.monotonic() - t0) < self.max_settle_wait_s: + # try: + # u_read = self.__get_current() + # if abs(u_read - u_cmd) <= self.tolerance: + # return + # except Exception as ex: + # last_exc = ex + # time.sleep(0.1) + + # # If we time out, ensure device is still enabled then raise + # self.__validate_status() + # detail = (f"set {u_cmd} but read {u_read} (±{self.tolerance})" + # if u_read is not None else str(last_exc)) + # # at end of _verify_after_set + # logger.warning(f"Actuator verification failed: set {u_cmd} read {u_read} (±{self.tolerance})" if u_read is not None else "Actuator verification failed (no read)") + # return + + # # raise ThrowReply('service_error_invalid_value', f'Actuator verification failed: {detail}') \ No newline at end of file diff --git a/dripline/extensions/pid_loop/plot_pid_log.py b/dripline/extensions/pid_loop/plot_pid_log.py new file mode 100644 index 0000000..a3ed6e5 --- /dev/null +++ b/dripline/extensions/pid_loop/plot_pid_log.py @@ -0,0 +1,55 @@ +import csv +import glob +import os +from datetime import datetime +import matplotlib.pyplot as plt + +log_dir = "./logs" +csv_files = glob.glob(os.path.join(log_dir, "pid_log*.csv")) + +for csv_file in csv_files: + times, PV, SP, throttle = [], [], [], [] + + with open(csv_file, "r") as f: + reader = csv.reader(f) + for row in reader: + # assuming column order: time, PV, SP, throttle + try: + times.append(datetime.fromisoformat(row[0])) + PV.append(float(row[1])) + SP.append(float(row[2])) + throttle.append(float(row[3])) + except Exception as e: + print(f"Skipping row in {csv_file}: {row}, error={e}") + + if not times: + print(f"Skipping {csv_file}, no valid data") + continue + + # Use filename (without extension) as title + title_str = os.path.basename(csv_file).replace(".csv", "") + + # Sensor vs Setpoint + plt.figure() + plt.plot(times, PV, 'ro', label="PV (sensor)") + plt.plot(times, SP, label="SP (setpoint)", linestyle="--") + plt.xlabel("Time") + plt.ylabel("Sensor Value") + plt.title(f"{title_str}: Sensor vs Setpoint") + plt.legend() + plt.grid(True) + plt.savefig(f"{title_str}_sensor.png") + plt.close() + + # Throttle vs Time + plt.figure() + plt.plot(times, throttle, 'go', label="Throttle (actuator)") + plt.xlabel("Time") + plt.ylabel("Throttle") + plt.title(f"{title_str}: Throttle") + plt.legend() + plt.grid(True) + plt.savefig(f"{title_str}_throttle.png") + plt.close() + +print("Plots saved for all CSV files in logs/") diff --git a/dripline/extensions/pid_loop_tester/__init__.py b/dripline/extensions/pid_loop_tester/__init__.py new file mode 100644 index 0000000..0fc838f --- /dev/null +++ b/dripline/extensions/pid_loop_tester/__init__.py @@ -0,0 +1,5 @@ +__all__ = [] + +# Modules in this directory +from .pid_loop_tester_v2 import * + diff --git a/dripline/extensions/pid_loop_tester/pid_loop_tester.py b/dripline/extensions/pid_loop_tester/pid_loop_tester.py new file mode 100644 index 0000000..dbbed21 --- /dev/null +++ b/dripline/extensions/pid_loop_tester/pid_loop_tester.py @@ -0,0 +1,137 @@ +''' +Implementation of a PID loop tester for the Dripline framework. +This module provides a service that can be used to test PID control loops by simulating +the behavior of a system of heaters and sensors. +''' +from __future__ import print_function +__all__ = [] + +from dripline.core import Service, ThrowReply +import math +import logging +logger = logging.getLogger(__name__) +logger.setLevel(logging.INFO) + +from time import sleep + +__all__.append('PidLoopTester') + +class PidLoopTester(Service): + ''' + A service that simulates hardware and endpoints for testing PID control loops. + Uses KeyValueStore to manage states, just using a velocity regulation example Ali posted in the slack. + ''' + + def __init__(self, + drag=0.1, + time_step=0.1, + time=0.0, + v0=0.0, + a0=0.0, + read_field='value_cal', + throttle_endpoint=None, + sensor_endpoint=None, + **kwargs + ): + ''' + T0 (float): + ''' + Service.__init__(self, **kwargs) + + self._drag = drag + self._throttle_endpoint = throttle_endpoint + self._sensor_endpoint = sensor_endpoint + self._time_step = time_step + self._time = time + self._read_field = read_field + + self.set_sensor_value(v0) # TODO: this should be a dictionary + self.set_throttle_value(a0) + + while True: + self.time_step() + sleep(self._time_step) + + + def get_sensor_value(self): + ''' + Get value from sensor endpoint. + ''' + if self._sensor_endpoint is None: + raise ThrowReply("No sensor endpoint configured") + return self.get(self._sensor_endpoint)[self._read_field] + + def set_sensor_value(self, value): + ''' + Set value to sensor endpoint. + ''' + if self._sensor_endpoint is None: + raise ThrowReply("No sensor endpoint configured") + self.set(self._sensor_endpoint, value) + + def get_throttle_value(self): + ''' + Get value from throttle endpoint. + ''' + if self._throttle_endpoint is None: + raise ThrowReply("No throttle endpoint configured") + return self.get(self._throttle_endpoint)[self._read_field] + + def set_throttle_value(self, value): + ''' + Set value to throttle endpoint. + ''' + if self._throttle_endpoint is None: + raise ThrowReply("No throttle endpoint configured") + self.set(self._throttle_endpoint, value) + + def external_disturbance(self, t): + ''' + Simulate an external disturbance to the system. + + Args: + t (float): Time at which the disturbance occurs. + ''' + # Example disturbance logic, can be customized + if 10 < t < 15: + return -1.0 # cooling event + elif 20 < t < 25: + return +0.5 # heating event + elif t > 40: + return (0.2 * math.sin(t)) # oscillating background + else: + return 0.0 + return disturbance + + def time_step(self): + ''' + Simulate a time step in the PID loop. + + Args: + dt (float): Time step duration. + ''' + # Simulate the system behavior based on the PID parameters and current state + v = self.get_sensor_value() + a_throttle = self.get_throttle_value() + + # Update the sensor value based on the heater value and system parameters + # thermal parameters + C = 10.0 # heat capacity + k = 0.1 # thermal loss rate + T_env = 40.0 # ambient temperature (in Kelvin) + + # heater power = throttle input + P_heater = a_throttle + + # cooling power = proportional to (T - T_env) + P_loss = k * (v - T_env) + + # Euler integration step + dT = (P_heater - P_loss) / C * self._time_step + new_v = v + dT + self.external_disturbance(self._time) + + new_v = a_throttle + self._drag * v + self.external_disturbance(self._time) + + self.set_sensor_value(new_v) + logger.info(f'FROM TESTER: time: {self._time:.2f}, sensor value: {new_v:.4f}, throttle value: {a_throttle:.4f}') + self._time += self._time_step diff --git a/dripline/extensions/pid_loop_tester/pid_loop_tester_v2.py b/dripline/extensions/pid_loop_tester/pid_loop_tester_v2.py new file mode 100644 index 0000000..7634b9b --- /dev/null +++ b/dripline/extensions/pid_loop_tester/pid_loop_tester_v2.py @@ -0,0 +1,230 @@ +""" +Implementation of a PID loop tester for the Dripline framework. +This module provides a service that can be used to test PID control loops by simulating +the behavior of a system of heaters and sensors. + +Thermal plant (1-R-1-C): + C dT/dt = P_heater(t) - (T - T_env)/R_th + D(t) + +Throttle mapping: + - throttle_mode="current": P = eta * R_heater * clamp(I,0,I_max)^2 + - throttle_mode="power" : P = clamp(P,0,P_max) +""" +from __future__ import print_function +__all__ = [] + +from dripline.core import Service, ThrowReply +import math +import logging +logger = logging.getLogger(__name__) +logger.setLevel(logging.INFO) + +from time import sleep + +__all__.append('PidLoopTester') + +class PidLoopTester(Service): + ''' + A service that simulates hardware endpoints for testing PID control loops. + Uses KeyValueStore to manage states. + + Endpoints: + - throttle_endpoint: controller writes throttle (current [A] or power [W]) + - sensor_endpoint : tester writes simulated sensor temperature [K] + ''' + + def __init__(self, + # ---- Simulation timing ---- + time_step=0.1, + time=0.0, + + # ---- Initial condition ---- + T0=40.0, # initial sensor temperature [K] + + # ---- Thermal model (1R1C) ---- + C=10.0, # heat capacity [J/K] + R_th=1.0, # thermal resistance to bath [K/W] + T_env=40.0, # bath/ambient temperature [K] + + # ---- Actuator/throttle mapping ---- + I_0=0.0, # initial current [A] + throttle_mode='current',# 'current' (A) or 'power' (W) + I_max=2.5, # A, clamp for current mode + R_heater=6.0, # ohms, for current mode power = eta * R_heater * I^2 + eta=0.95, # efficiency into modeled node(s) + P_max=100.0, # W, clamp for power mode (ignored in current mode) + + # ---- I/O plumbing ---- + read_field='value_cal', + throttle_endpoint=None, + sensor_endpoint=None, + + # ---- Extras ---- + enable_disturbance=True, + + **kwargs + ): + ''' + Args: + time_step (float): integration step [s] + T0 (float): initial sensor temperature [K] + C (float): heat capacity [J/K] + R_th (float): thermal resistance to bath [K/W] + T_env (float): bath temperature [K] + throttle_mode (str): 'current' or 'power' + I_max (float): current clamp [A] + R_heater (float): heater resistance [ohm] + eta (float): electrical->thermal efficiency (0..1) + P_max (float): power clamp [W] for power mode + read_field (str): field name stored in KVS dicts + throttle_endpoint (str): KVS key for throttle + sensor_endpoint (str): KVS key for sensor + enable_disturbance (bool): toggle external disturbance term + ''' + Service.__init__(self, **kwargs) + + # Timing / state + self._dt = float(time_step) + self._time = float(time) + + # Plant params + self._C = float(C) + self._Rth = float(R_th) + self._Tenv = float(T_env) + + # Actuator map + self._mode = str(throttle_mode).lower() + self._Imax = float(I_max) + self._Rheater = float(R_heater) + self._eta = float(eta) + self._Pmax = float(P_max) + + # I/O + self._read_field = read_field + self._throttle_endpoint = throttle_endpoint + self._sensor_endpoint = sensor_endpoint + + # Disturbance toggle + self._enable_disturbance = bool(enable_disturbance) + + # Initialize endpoints + if self._sensor_endpoint is None or self._throttle_endpoint is None: + raise ThrowReply("Both sensor_endpoint and throttle_endpoint must be configured") + + self.set_sensor_value(T0) # temperature [K] + # Initialize throttle to 0 (safe) + self.set_throttle_value(I_0) + + # Main loop + while True: + self.time_step() + sleep(self._dt) + + # ------------------ KVS helpers ------------------ + + def get_sensor_value(self): + ''' + Get temperature [K] from sensor endpoint. + ''' + if self._sensor_endpoint is None: + raise ThrowReply("No sensor endpoint configured") + return self.get(self._sensor_endpoint)[self._read_field] + + def set_sensor_value(self, value): + ''' + Set temperature [K] to sensor endpoint. + ''' + if self._sensor_endpoint is None: + raise ThrowReply("No sensor endpoint configured") + self.set(self._sensor_endpoint, value) + self._Tenv = value + + def get_throttle_value(self): + ''' + Get throttle from throttle endpoint (A in 'current' mode, W in 'power' mode). + ''' + if self._throttle_endpoint is None: + raise ThrowReply("No throttle endpoint configured") + return self.get(self._throttle_endpoint)[self._read_field] + + def set_throttle_value(self, value): + ''' + Set throttle to throttle endpoint. + ''' + if self._throttle_endpoint is None: + raise ThrowReply("No throttle endpoint configured") + self.set(self._throttle_endpoint, value) + + # ------------------ Disturbance model ------------------ + + def external_disturbance(self, t): + ''' + External disturbance power D(t) [W]. Positive -> heating, negative -> cooling. + Feel free to customize. + ''' + if not self._enable_disturbance: + return 0.0 + + if 10.0 < t < 15.0: + return -1.0 # brief cooling event + elif 20.0 < t < 25.0: + return +0.5 # brief heating event + elif t > 40.0: + return 0.2 * math.sin(t) # slow oscillating background + else: + return 0.0 + + # ------------------ Actuator mapping ------------------ + + def _power_from_throttle(self, throttle_value): + ''' + Map throttle to heater power [W]. + - current mode: throttle=I[A] -> P=eta*R_heater*I^2 + - power mode: throttle=P[W] (clamped) + ''' + if self._mode == 'current': + I = max(0.0, min(self._Imax, float(throttle_value))) + return self._eta * self._Rheater * (I ** 2) + elif self._mode == 'power': + return max(0.0, min(self._Pmax, float(throttle_value))) + else: + raise ThrowReply("throttle_mode must be 'current' or 'power'") + + # ------------------ Simulation step ------------------ + + def time_step(self): + ''' + Advance the thermal plant by dt using forward Euler. + C dT/dt = P_heater - (T - T_env)/R_th + D(t) + ''' + # Read current state and command with error handling + try: + T = float(self.get_sensor_value()) # [K] + throttle = float(self.get_throttle_value()) # [A] or [W] depending on mode + except Exception as e: + logger.warning(f"Failed to read endpoints, using default values: {e}") + T = self._Tenv # Use ambient temperature as fallback + throttle = 0.0 # Use zero throttle as fallback + + # Heater power (W) + P_heater = self._power_from_throttle(throttle) + + # Heat loss to bath (positive when T > T_env) + P_loss = (T - self._Tenv) / self._Rth # [W] + + # External disturbance (W) + D = self.external_disturbance(self._time) + + # Integrate temperature + dT_dt = (P_heater - P_loss + D) / self._C + T_new = T + self._dt * dT_dt + + # Write back & log + self.set_sensor_value(T_new) + logger.info( + f'FROM TESTER: t={self._time:.2f}s, T={T_new:.3f} K, ' + f'throttle={throttle:.4f} ({self._mode}), P={P_heater:.3f} W, D={D:.3f} W' + ) + + # Advance sim time + self._time += self._dt \ No newline at end of file From 20cd2e55df0b7c5cb67ebb46de4d9dc1d3fb741e Mon Sep 17 00:00:00 2001 From: Yao Yin Date: Tue, 14 Oct 2025 20:34:56 -0700 Subject: [PATCH 02/10] Enable heater channel before running everything else - bug fix --- dripline/extensions/pid_loop/pid_loop_v2.py | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/dripline/extensions/pid_loop/pid_loop_v2.py b/dripline/extensions/pid_loop/pid_loop_v2.py index 75f6b8f..a0529ef 100644 --- a/dripline/extensions/pid_loop/pid_loop_v2.py +++ b/dripline/extensions/pid_loop/pid_loop_v2.py @@ -138,6 +138,15 @@ def __init__(self, # Forcing reprocess on SP change (as in the original) self._force_reprocess = False + # Set status channel to 1 to enable heater output before anything else + logger.info(f"Setting {self._status_channel} to 1 to enable heater output") + try: + self.set(self._status_channel, 1) + logger.info(f"Successfully set {self._status_channel} to 1") + except Exception as ex: + logger.error(f"Failed to set {self._status_channel} to 1: {ex}") + raise + # Verify device state and seed last output self.__validate_status() self._old_current = self.__get_current() From 5703113d19533a609586490c7d66b67a35908190 Mon Sep 17 00:00:00 2001 From: Yao Yin Date: Tue, 14 Oct 2025 21:00:22 -0700 Subject: [PATCH 03/10] Ohm Kelvin conversion --- dripline/extensions/pid_loop/pid_loop_v2.py | 73 ++++++++++++++++++++- 1 file changed, 72 insertions(+), 1 deletion(-) diff --git a/dripline/extensions/pid_loop/pid_loop_v2.py b/dripline/extensions/pid_loop/pid_loop_v2.py index a0529ef..dc58ea1 100644 --- a/dripline/extensions/pid_loop/pid_loop_v2.py +++ b/dripline/extensions/pid_loop/pid_loop_v2.py @@ -47,6 +47,64 @@ def clamp(x: float, lo: float, hi: float) -> float: return lo if x < lo else hi if x > hi else x +def pt100_resistance_to_kelvin(resistance: float) -> float: + """ + Convert PT100 resistance (ohms) to temperature (Kelvin). + + Uses the Callendar-Van Dusen equation for PT100 sensors. + Valid for temperatures from approximately -200°C to +850°C. + + Parameters + ---------- + resistance : float + Resistance in ohms + + Returns + ------- + float + Temperature in Kelvin + + Notes + ----- + PT100 standard (IEC 60751): + - R0 = 100 Ω at 0°C + - α = 0.00385 Ω/Ω/°C (most common, European standard) + + For temperatures above 0°C: + R(T) = R0 * (1 + A*T + B*T²) + where A = 3.9083e-3, B = -5.775e-7 + + For temperatures below 0°C, additional terms are needed, + but for cryogenic work above -200°C this approximation is sufficient. + """ + import math + + # PT100 coefficients (IEC 60751) + R0 = 100.0 # Resistance at 0°C (ohms) + A = 3.9083e-3 # Temperature coefficient (1/°C) + B = -5.775e-7 # Temperature coefficient (1/°C²) + + # Solve quadratic equation: R = R0*(1 + A*T + B*T²) + # Rearranged: B*T² + A*T + (1 - R/R0) = 0 + + a = B + b = A + c = 1.0 - (resistance / R0) + + discriminant = b*b - 4*a*c + + if discriminant < 0: + raise ValueError(f"Invalid resistance value {resistance}Ω for PT100 sensor") + + # Use the positive root (physical solution) + temp_celsius = (-b + math.sqrt(discriminant)) / (2*a) + + # Convert to Kelvin + temp_kelvin = temp_celsius + 273.15 + + return temp_kelvin + + class PidController(Service): """ PID control loop Service (positional PID form with optional baseline offset). @@ -86,6 +144,7 @@ def __init__(self, derivative_smoothing: float = 0.0, # EMA factor in [0,1]; 0 = off max_settle_wait_s: float = 3.0, # bounded verify-after-set u_offset_baseline: float = 0.0, # explicit baseline if offset term desired + convert_pt100: bool = False, # Convert PT100 resistance to Kelvin **kwargs): """ Initialize the PID controller and runtime state. @@ -107,6 +166,7 @@ def __init__(self, self._status_channel = status_channel self.payload_field = payload_field self.tolerance = float(tolerance) + self._convert_pt100 = bool(convert_pt100) # Controller gains and setpoint self._target_value = float(target_value) @@ -188,11 +248,22 @@ def _poll_sensor_loop(self) -> None: continue # Extract PV this_value = resp.get(self.payload_field) - logger.info(f"Message payload value: {this_value}") + logger.info(f"Message payload value (raw): {this_value}") if this_value is None: logger.info('value is None') time.sleep(self._poll_period_s) continue + + # Convert from PT100 resistance to temperature if enabled + if self._convert_pt100: + try: + resistance_ohms = float(this_value) + this_value = pt100_resistance_to_kelvin(resistance_ohms) + logger.info(f"PT100 conversion: {resistance_ohms:.2f}Ω -> {this_value:.2f}K ({this_value-273.15:.2f}°C)") + except (ValueError, TypeError) as ex: + logger.error(f"PT100 conversion failed for {this_value}: {ex}") + time.sleep(self._poll_period_s) + continue # 2) Parse timestamp robustly (keep your original format first) ts_raw = None From 45e4c0ce2ec0c9b8292d612b47473fb075fd591a Mon Sep 17 00:00:00 2001 From: Yao Yin Date: Tue, 14 Oct 2025 21:15:53 -0700 Subject: [PATCH 04/10] Voltage channel, conversion from ohm to kelvins --- dripline/extensions/pid_loop/pid_loop_v2.py | 62 ++++++++++----------- 1 file changed, 30 insertions(+), 32 deletions(-) diff --git a/dripline/extensions/pid_loop/pid_loop_v2.py b/dripline/extensions/pid_loop/pid_loop_v2.py index dc58ea1..f2f7521 100644 --- a/dripline/extensions/pid_loop/pid_loop_v2.py +++ b/dripline/extensions/pid_loop/pid_loop_v2.py @@ -51,8 +51,8 @@ def pt100_resistance_to_kelvin(resistance: float) -> float: """ Convert PT100 resistance (ohms) to temperature (Kelvin). - Uses the Callendar-Van Dusen equation for PT100 sensors. - Valid for temperatures from approximately -200°C to +850°C. + Uses a custom calibration curve specific to the RTD01 sensor, + fitted from actual sensor data in the cryogenic operating range. Parameters ---------- @@ -66,41 +66,27 @@ def pt100_resistance_to_kelvin(resistance: float) -> float: Notes ----- - PT100 standard (IEC 60751): - - R0 = 100 Ω at 0°C - - α = 0.00385 Ω/Ω/°C (most common, European standard) + Calibration curve fitted from RTD01.Front.Cavity.Thermal sensor data: + T(K) = a*R² + b*R + c - For temperatures above 0°C: - R(T) = R0 * (1 + A*T + B*T²) - where A = 3.9083e-3, B = -5.775e-7 + Calibrated range: ~14.4-15.2 Ω (62.5-64.0 K) + Based on synchronized Ohm and K channel measurements. - For temperatures below 0°C, additional terms are needed, - but for cryogenic work above -200°C this approximation is sufficient. + For resistance values outside the calibrated range, the polynomial + is extrapolated (may be less accurate). """ - import math + # Custom calibration coefficients for RTD01 sensor + # Fitted from actual sensor data: T(K) = a*R² + b*R + c + a = 0.059524 + b = 0.178571 + c = 47.628423 - # PT100 coefficients (IEC 60751) - R0 = 100.0 # Resistance at 0°C (ohms) - A = 3.9083e-3 # Temperature coefficient (1/°C) - B = -5.775e-7 # Temperature coefficient (1/°C²) + # Apply polynomial calibration + temp_kelvin = a * resistance**2 + b * resistance + c - # Solve quadratic equation: R = R0*(1 + A*T + B*T²) - # Rearranged: B*T² + A*T + (1 - R/R0) = 0 - - a = B - b = A - c = 1.0 - (resistance / R0) - - discriminant = b*b - 4*a*c - - if discriminant < 0: - raise ValueError(f"Invalid resistance value {resistance}Ω for PT100 sensor") - - # Use the positive root (physical solution) - temp_celsius = (-b + math.sqrt(discriminant)) / (2*a) - - # Convert to Kelvin - temp_kelvin = temp_celsius + 273.15 + # Sanity check: warn if outside typical calibrated range + if resistance < 10.0 or resistance > 40.0: + logger.warning(f"Resistance {resistance:.2f}Ω is outside typical PT100 range") return temp_kelvin @@ -127,6 +113,7 @@ def __init__(self, output_channel: str, check_channel: str, status_channel: str, + voltage_channel: str, payload_field: str = 'value_cal', tolerance: float = 0.01, target_value: float = 85.0, @@ -164,6 +151,7 @@ def __init__(self, self._set_channel = output_channel self._check_channel = check_channel self._status_channel = status_channel + self._voltage_channel = voltage_channel self.payload_field = payload_field self.tolerance = float(tolerance) self._convert_pt100 = bool(convert_pt100) @@ -207,6 +195,16 @@ def __init__(self, logger.error(f"Failed to set {self._status_channel} to 1: {ex}") raise + # Set voltage channel to 30V if provided + if self._voltage_channel is not None: + logger.info(f"Setting {self._voltage_channel} to 30V") + try: + self.set(self._voltage_channel, 30.0) + logger.info(f"Successfully set {self._voltage_channel} to 30V") + except Exception as ex: + logger.error(f"Failed to set {self._voltage_channel} to 30V: {ex}") + raise + # Verify device state and seed last output self.__validate_status() self._old_current = self.__get_current() From c323f2a390819416e26fc9292d65a2a9427775bf Mon Sep 17 00:00:00 2001 From: Yao Yin Date: Wed, 12 Nov 2025 17:11:44 -0800 Subject: [PATCH 05/10] Add small debug statement --- dripline/extensions/pid_loop/pid_loop_v2.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/dripline/extensions/pid_loop/pid_loop_v2.py b/dripline/extensions/pid_loop/pid_loop_v2.py index f2f7521..0680bf0 100644 --- a/dripline/extensions/pid_loop/pid_loop_v2.py +++ b/dripline/extensions/pid_loop/pid_loop_v2.py @@ -125,7 +125,7 @@ def __init__(self, delta_out_min: float = 0.001, # Minimum current change enable_offset_term: bool = False, # Use old current as baseline minimum_elapsed_time: float = 0.0, - poll_period_s: float = 0.1, # NEW: polling period for input_channel + poll_period_s: float = 1.0, # NEW: polling period for input_channel # --- New, optional, backward-compatible knobs below --- integral_limit: Optional[float] = None, # |integral(e) dt| cap for anti-windup derivative_smoothing: float = 0.0, # EMA factor in [0,1]; 0 = off @@ -583,6 +583,7 @@ def process_new_value(self, value: float, timestamp: datetime.datetime) -> None: return self.set_current(new_current) + logger.info(f"sent command to set current to {new_current}!!") # self._verify_after_set(new_current) # NEW: append log row From 490c1cc34fdeecc8213e00f51b57783c9e2fb571 Mon Sep 17 00:00:00 2001 From: Yao Yin Date: Fri, 14 Nov 2025 12:54:49 -0800 Subject: [PATCH 06/10] Clean up commented code, get rid of local logging --- dripline/extensions/pid_loop/pid_loop_v2.py | 136 +------------------- 1 file changed, 5 insertions(+), 131 deletions(-) diff --git a/dripline/extensions/pid_loop/pid_loop_v2.py b/dripline/extensions/pid_loop/pid_loop_v2.py index 0680bf0..c3adf82 100644 --- a/dripline/extensions/pid_loop/pid_loop_v2.py +++ b/dripline/extensions/pid_loop/pid_loop_v2.py @@ -47,50 +47,6 @@ def clamp(x: float, lo: float, hi: float) -> float: return lo if x < lo else hi if x > hi else x -def pt100_resistance_to_kelvin(resistance: float) -> float: - """ - Convert PT100 resistance (ohms) to temperature (Kelvin). - - Uses a custom calibration curve specific to the RTD01 sensor, - fitted from actual sensor data in the cryogenic operating range. - - Parameters - ---------- - resistance : float - Resistance in ohms - - Returns - ------- - float - Temperature in Kelvin - - Notes - ----- - Calibration curve fitted from RTD01.Front.Cavity.Thermal sensor data: - T(K) = a*R² + b*R + c - - Calibrated range: ~14.4-15.2 Ω (62.5-64.0 K) - Based on synchronized Ohm and K channel measurements. - - For resistance values outside the calibrated range, the polynomial - is extrapolated (may be less accurate). - """ - # Custom calibration coefficients for RTD01 sensor - # Fitted from actual sensor data: T(K) = a*R² + b*R + c - a = 0.059524 - b = 0.178571 - c = 47.628423 - - # Apply polynomial calibration - temp_kelvin = a * resistance**2 + b * resistance + c - - # Sanity check: warn if outside typical calibrated range - if resistance < 10.0 or resistance > 40.0: - logger.warning(f"Resistance {resistance:.2f}Ω is outside typical PT100 range") - - return temp_kelvin - - class PidController(Service): """ PID control loop Service (positional PID form with optional baseline offset). @@ -113,7 +69,6 @@ def __init__(self, output_channel: str, check_channel: str, status_channel: str, - voltage_channel: str, payload_field: str = 'value_cal', tolerance: float = 0.01, target_value: float = 85.0, @@ -125,13 +80,12 @@ def __init__(self, delta_out_min: float = 0.001, # Minimum current change enable_offset_term: bool = False, # Use old current as baseline minimum_elapsed_time: float = 0.0, - poll_period_s: float = 1.0, # NEW: polling period for input_channel + poll_period_s: float = 0.1, # NEW: polling period for input_channel # --- New, optional, backward-compatible knobs below --- integral_limit: Optional[float] = None, # |integral(e) dt| cap for anti-windup derivative_smoothing: float = 0.0, # EMA factor in [0,1]; 0 = off max_settle_wait_s: float = 3.0, # bounded verify-after-set u_offset_baseline: float = 0.0, # explicit baseline if offset term desired - convert_pt100: bool = False, # Convert PT100 resistance to Kelvin **kwargs): """ Initialize the PID controller and runtime state. @@ -151,10 +105,8 @@ def __init__(self, self._set_channel = output_channel self._check_channel = check_channel self._status_channel = status_channel - self._voltage_channel = voltage_channel self.payload_field = payload_field self.tolerance = float(tolerance) - self._convert_pt100 = bool(convert_pt100) # Controller gains and setpoint self._target_value = float(target_value) @@ -186,25 +138,6 @@ def __init__(self, # Forcing reprocess on SP change (as in the original) self._force_reprocess = False - # Set status channel to 1 to enable heater output before anything else - logger.info(f"Setting {self._status_channel} to 1 to enable heater output") - try: - self.set(self._status_channel, 1) - logger.info(f"Successfully set {self._status_channel} to 1") - except Exception as ex: - logger.error(f"Failed to set {self._status_channel} to 1: {ex}") - raise - - # Set voltage channel to 30V if provided - if self._voltage_channel is not None: - logger.info(f"Setting {self._voltage_channel} to 30V") - try: - self.set(self._voltage_channel, 30.0) - logger.info(f"Successfully set {self._voltage_channel} to 30V") - except Exception as ex: - logger.error(f"Failed to set {self._voltage_channel} to 30V: {ex}") - raise - # Verify device state and seed last output self.__validate_status() self._old_current = self.__get_current() @@ -246,22 +179,11 @@ def _poll_sensor_loop(self) -> None: continue # Extract PV this_value = resp.get(self.payload_field) - logger.info(f"Message payload value (raw): {this_value}") + logger.info(f"Message payload value: {this_value}") if this_value is None: logger.info('value is None') time.sleep(self._poll_period_s) continue - - # Convert from PT100 resistance to temperature if enabled - if self._convert_pt100: - try: - resistance_ohms = float(this_value) - this_value = pt100_resistance_to_kelvin(resistance_ohms) - logger.info(f"PT100 conversion: {resistance_ohms:.2f}Ω -> {this_value:.2f}K ({this_value-273.15:.2f}°C)") - except (ValueError, TypeError) as ex: - logger.error(f"PT100 conversion failed for {this_value}: {ex}") - time.sleep(self._poll_period_s) - continue # 2) Parse timestamp robustly (keep your original format first) ts_raw = None @@ -316,20 +238,8 @@ def _log_append(self, timestamp: datetime.datetime, pv: float, sp: float, u: flo if len(self._log_data) >= self._log_autoflush_every: need_flush = True if need_flush: - self._flush_log_to_csv() - - # def save_log(self, filename: Optional[str] = None) -> None: - # """ - # Public method: force a flush of the in-memory log buffer to CSV. - # If 'filename' is provided, switch output file and reset header handling. - # """ - # if filename: - # with self._log_lock: - # # If the filename changes, re-initialize header for the new file - # if filename != self._log_filename: - # self._log_filename = filename - # self._log_file_initialized = False - # self._flush_log_to_csv() + pass # TODO: remove this later + # self._flush_log_to_csv() def _flush_log_to_csv(self) -> None: """ @@ -583,7 +493,7 @@ def process_new_value(self, value: float, timestamp: datetime.datetime) -> None: return self.set_current(new_current) - logger.info(f"sent command to set current to {new_current}!!") + logger.info(f"set current to {new_current!") # self._verify_after_set(new_current) # NEW: append log row @@ -593,39 +503,3 @@ def process_new_value(self, value: float, timestamp: datetime.datetime) -> None: f"u={new_current:.6f} (Kp={self.Kproportional}, Ki={self.Kintegral}, Kd={self.Kdifferential})") self._old_current = new_current - - # ------------------------------------------------------------------ # - # Private helpers (new, but do not change public surface) - # ------------------------------------------------------------------ # - - # def _verify_after_set(self, u_cmd: float) -> None: - # """ - # Poll check_channel up to max_settle_wait_s until |read - set| <= tolerance. - - # Raises - # ------ - # ThrowReply - # If actuator does not report the commanded value within the tolerance - # before timeout. Revalidates status before raising. - # """ - # t0 = time.monotonic() - # last_exc = None - # u_read = None - # while (time.monotonic() - t0) < self.max_settle_wait_s: - # try: - # u_read = self.__get_current() - # if abs(u_read - u_cmd) <= self.tolerance: - # return - # except Exception as ex: - # last_exc = ex - # time.sleep(0.1) - - # # If we time out, ensure device is still enabled then raise - # self.__validate_status() - # detail = (f"set {u_cmd} but read {u_read} (±{self.tolerance})" - # if u_read is not None else str(last_exc)) - # # at end of _verify_after_set - # logger.warning(f"Actuator verification failed: set {u_cmd} read {u_read} (±{self.tolerance})" if u_read is not None else "Actuator verification failed (no read)") - # return - - # # raise ThrowReply('service_error_invalid_value', f'Actuator verification failed: {detail}') \ No newline at end of file From 3228a54496e4738bc2938b4a05305deb23f62bbb Mon Sep 17 00:00:00 2001 From: Yao Yin Date: Fri, 14 Nov 2025 16:05:48 -0800 Subject: [PATCH 07/10] typo fix --- dripline/extensions/pid_loop/pid_loop_v2.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/dripline/extensions/pid_loop/pid_loop_v2.py b/dripline/extensions/pid_loop/pid_loop_v2.py index c3adf82..06bc28d 100644 --- a/dripline/extensions/pid_loop/pid_loop_v2.py +++ b/dripline/extensions/pid_loop/pid_loop_v2.py @@ -493,7 +493,7 @@ def process_new_value(self, value: float, timestamp: datetime.datetime) -> None: return self.set_current(new_current) - logger.info(f"set current to {new_current!") + logger.info(f"set current to {new_current!}") # self._verify_after_set(new_current) # NEW: append log row From 7f45f7154522e199217e9fdc2cbf697245645c8d Mon Sep 17 00:00:00 2001 From: Yao Yin Date: Fri, 14 Nov 2025 16:06:57 -0800 Subject: [PATCH 08/10] typo fix --- dripline/extensions/pid_loop/pid_loop_v2.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/dripline/extensions/pid_loop/pid_loop_v2.py b/dripline/extensions/pid_loop/pid_loop_v2.py index 06bc28d..3c2c8a5 100644 --- a/dripline/extensions/pid_loop/pid_loop_v2.py +++ b/dripline/extensions/pid_loop/pid_loop_v2.py @@ -493,7 +493,7 @@ def process_new_value(self, value: float, timestamp: datetime.datetime) -> None: return self.set_current(new_current) - logger.info(f"set current to {new_current!}") + logger.info(f"set current to {new_current}!") # self._verify_after_set(new_current) # NEW: append log row From d02d1490e88fddd599efa4086d1fc22bf34b6c9f Mon Sep 17 00:00:00 2001 From: Yao Yin Date: Fri, 14 Nov 2025 16:15:31 -0800 Subject: [PATCH 09/10] revert to previous code, accidentally overwritten --- dripline/extensions/pid_loop/pid_loop_v2.py | 85 ++++++++++++++++++++- 1 file changed, 82 insertions(+), 3 deletions(-) diff --git a/dripline/extensions/pid_loop/pid_loop_v2.py b/dripline/extensions/pid_loop/pid_loop_v2.py index 3c2c8a5..9c2dd83 100644 --- a/dripline/extensions/pid_loop/pid_loop_v2.py +++ b/dripline/extensions/pid_loop/pid_loop_v2.py @@ -47,6 +47,50 @@ def clamp(x: float, lo: float, hi: float) -> float: return lo if x < lo else hi if x > hi else x +def pt100_resistance_to_kelvin(resistance: float) -> float: + """ + Convert PT100 resistance (ohms) to temperature (Kelvin). + + Uses a custom calibration curve specific to the RTD01 sensor, + fitted from actual sensor data in the cryogenic operating range. + + Parameters + ---------- + resistance : float + Resistance in ohms + + Returns + ------- + float + Temperature in Kelvin + + Notes + ----- + Calibration curve fitted from RTD01.Front.Cavity.Thermal sensor data: + T(K) = a*R² + b*R + c + + Calibrated range: ~14.4-15.2 Ω (62.5-64.0 K) + Based on synchronized Ohm and K channel measurements. + + For resistance values outside the calibrated range, the polynomial + is extrapolated (may be less accurate). + """ + # Custom calibration coefficients for RTD01 sensor + # Fitted from actual sensor data: T(K) = a*R² + b*R + c + a = 0.059524 + b = 0.178571 + c = 47.628423 + + # Apply polynomial calibration + temp_kelvin = a * resistance**2 + b * resistance + c + + # Sanity check: warn if outside typical calibrated range + if resistance < 10.0 or resistance > 40.0: + logger.warning(f"Resistance {resistance:.2f}Ω is outside typical PT100 range") + + return temp_kelvin + + class PidController(Service): """ PID control loop Service (positional PID form with optional baseline offset). @@ -69,6 +113,7 @@ def __init__(self, output_channel: str, check_channel: str, status_channel: str, + voltage_channel: str, payload_field: str = 'value_cal', tolerance: float = 0.01, target_value: float = 85.0, @@ -80,12 +125,13 @@ def __init__(self, delta_out_min: float = 0.001, # Minimum current change enable_offset_term: bool = False, # Use old current as baseline minimum_elapsed_time: float = 0.0, - poll_period_s: float = 0.1, # NEW: polling period for input_channel + poll_period_s: float = 1.0, # NEW: polling period for input_channel # --- New, optional, backward-compatible knobs below --- integral_limit: Optional[float] = None, # |integral(e) dt| cap for anti-windup derivative_smoothing: float = 0.0, # EMA factor in [0,1]; 0 = off max_settle_wait_s: float = 3.0, # bounded verify-after-set u_offset_baseline: float = 0.0, # explicit baseline if offset term desired + convert_pt100: bool = False, # Convert PT100 resistance to Kelvin **kwargs): """ Initialize the PID controller and runtime state. @@ -105,8 +151,10 @@ def __init__(self, self._set_channel = output_channel self._check_channel = check_channel self._status_channel = status_channel + self._voltage_channel = voltage_channel self.payload_field = payload_field self.tolerance = float(tolerance) + self._convert_pt100 = bool(convert_pt100) # Controller gains and setpoint self._target_value = float(target_value) @@ -138,6 +186,25 @@ def __init__(self, # Forcing reprocess on SP change (as in the original) self._force_reprocess = False + # Set status channel to 1 to enable heater output before anything else + logger.info(f"Setting {self._status_channel} to 1 to enable heater output") + try: + self.set(self._status_channel, 1) + logger.info(f"Successfully set {self._status_channel} to 1") + except Exception as ex: + logger.error(f"Failed to set {self._status_channel} to 1: {ex}") + raise + + # Set voltage channel to 30V if provided + if self._voltage_channel is not None: + logger.info(f"Setting {self._voltage_channel} to 30V") + try: + self.set(self._voltage_channel, 30.0) + logger.info(f"Successfully set {self._voltage_channel} to 30V") + except Exception as ex: + logger.error(f"Failed to set {self._voltage_channel} to 30V: {ex}") + raise + # Verify device state and seed last output self.__validate_status() self._old_current = self.__get_current() @@ -179,11 +246,22 @@ def _poll_sensor_loop(self) -> None: continue # Extract PV this_value = resp.get(self.payload_field) - logger.info(f"Message payload value: {this_value}") + logger.info(f"Message payload value (raw): {this_value}") if this_value is None: logger.info('value is None') time.sleep(self._poll_period_s) continue + + # Convert from PT100 resistance to temperature if enabled + if self._convert_pt100: + try: + resistance_ohms = float(this_value) + this_value = pt100_resistance_to_kelvin(resistance_ohms) + logger.info(f"PT100 conversion: {resistance_ohms:.2f}Ω -> {this_value:.2f}K ({this_value-273.15:.2f}°C)") + except (ValueError, TypeError) as ex: + logger.error(f"PT100 conversion failed for {this_value}: {ex}") + time.sleep(self._poll_period_s) + continue # 2) Parse timestamp robustly (keep your original format first) ts_raw = None @@ -241,6 +319,7 @@ def _log_append(self, timestamp: datetime.datetime, pv: float, sp: float, u: flo pass # TODO: remove this later # self._flush_log_to_csv() + def _flush_log_to_csv(self) -> None: """ Flush the buffered rows to CSV (append mode). Writes header once per file. @@ -493,7 +572,7 @@ def process_new_value(self, value: float, timestamp: datetime.datetime) -> None: return self.set_current(new_current) - logger.info(f"set current to {new_current}!") + logger.info(f"sent command to set current to {new_current}!!") # self._verify_after_set(new_current) # NEW: append log row From d04b15e8add9b699e64d4b36776613d77eece753 Mon Sep 17 00:00:00 2001 From: Yao Yin Date: Fri, 14 Nov 2025 16:30:12 -0800 Subject: [PATCH 10/10] add better temperature ohm conversion for high temp --- dripline/extensions/pid_loop/pid_loop_v2.py | 89 ++++++++++++--------- 1 file changed, 51 insertions(+), 38 deletions(-) diff --git a/dripline/extensions/pid_loop/pid_loop_v2.py b/dripline/extensions/pid_loop/pid_loop_v2.py index 9c2dd83..cc76af2 100644 --- a/dripline/extensions/pid_loop/pid_loop_v2.py +++ b/dripline/extensions/pid_loop/pid_loop_v2.py @@ -50,45 +50,58 @@ def clamp(x: float, lo: float, hi: float) -> float: def pt100_resistance_to_kelvin(resistance: float) -> float: """ Convert PT100 resistance (ohms) to temperature (Kelvin). - - Uses a custom calibration curve specific to the RTD01 sensor, - fitted from actual sensor data in the cryogenic operating range. - - Parameters - ---------- - resistance : float - Resistance in ohms - - Returns - ------- - float - Temperature in Kelvin - - Notes - ----- - Calibration curve fitted from RTD01.Front.Cavity.Thermal sensor data: - T(K) = a*R² + b*R + c - - Calibrated range: ~14.4-15.2 Ω (62.5-64.0 K) - Based on synchronized Ohm and K channel measurements. - - For resistance values outside the calibrated range, the polynomial - is extrapolated (may be less accurate). + + - For the RTD01 cryogenic region (R ≈ 14–15 Ω), use custom polynomial T(K). + - Otherwise, use standard IEC 60751 (Callendar–Van Dusen) high-T form + and pick the physically reasonable root. """ - # Custom calibration coefficients for RTD01 sensor - # Fitted from actual sensor data: T(K) = a*R² + b*R + c - a = 0.059524 - b = 0.178571 - c = 47.628423 - - # Apply polynomial calibration - temp_kelvin = a * resistance**2 + b * resistance + c - - # Sanity check: warn if outside typical calibrated range - if resistance < 10.0 or resistance > 40.0: - logger.warning(f"Resistance {resistance:.2f}Ω is outside typical PT100 range") - - return temp_kelvin + # --- 1. RTD01 custom cryogenic calibration (narrow range) --- + # Valid-ish window around your fit: adjust if you have better bounds + if 13.0 <= resistance <= 17.0: + a = 0.059524 + b = 0.178571 + c = 47.628423 + temp_K = a * resistance**2 + b * resistance + c + return temp_K + + # --- 2. Standard PT100 IEC 60751 (0–850 °C branch) --- + # R(T) = R0 * (1 + A*T + B*T^2) + R0 = 100.0 # Ω at 0 °C + A = 3.9083e-3 + B = -5.775e-7 + + Cq = 1.0 - (resistance / R0) + disc = A * A - 4.0 * B * Cq + if disc < 0: + logger.error( + f"PT100 conversion: negative discriminant for R={resistance:.2f}Ω" + ) + return float("nan") + + sqrt_disc = disc ** 0.5 + + # Two quadratic roots + T1 = (-A + sqrt_disc) / (2.0 * B) + T2 = (-A - sqrt_disc) / (2.0 * B) + + # Pick the physically reasonable root (within PT100 spec range) + candidates = [T for T in (T1, T2) if -200.0 <= T <= 850.0] + if not candidates: + logger.error( + f"PT100 conversion: no physical solution for R={resistance:.2f}Ω" + ) + return float("nan") + + T_celsius = candidates[0] + temp_K = T_celsius + 273.15 + + # Optional sanity log, but don't claim 108Ω is "outside PT100 range" + if resistance < 10.0 or resistance > 400.0: + logger.warning( + f"PT100 conversion: R={resistance:.2f}Ω is outside typical operating range" + ) + + return temp_K class PidController(Service):