{ "cells": [ { "cell_type": "markdown", "metadata": { "nbpages": { "level": 0, "link": "[](https://jckantor.github.io/cbe30338-2021/03.03-Relay-Control.html)", "section": "" } }, "source": [ "\n", "*This notebook contains material from [cbe30338-2021](https://jckantor.github.io/cbe30338-2021);\n", "content is available [on Github](https://github.com/jckantor/cbe30338-2021.git).*\n" ] }, { "cell_type": "markdown", "metadata": { "nbpages": { "level": 0, "link": "[](https://jckantor.github.io/cbe30338-2021/03.03-Relay-Control.html)", "section": "" } }, "source": [ "\n", "< [3.2 Setpoints](https://jckantor.github.io/cbe30338-2021/03.02-Setpoints.html) | [Contents](toc.html) | [Tag Index](tag_index.html) | [3.4 Implementing Controllers in Python](https://jckantor.github.io/cbe30338-2021/03.04-Implementing-Controllers.html) >

\"Open

\"Download\"" ] }, { "cell_type": "markdown", "metadata": { "nbpages": { "level": 1, "link": "[3.3 Relay Control](https://jckantor.github.io/cbe30338-2021/03.03-Relay-Control.html#3.3-Relay-Control)", "section": "3.3 Relay Control" } }, "source": [ "# 3.3 Relay Control" ] }, { "cell_type": "markdown", "metadata": { "nbpages": { "level": 2, "link": "[3.3.1 Relay Control for the Temperature Control Lab](https://jckantor.github.io/cbe30338-2021/03.03-Relay-Control.html#3.3.1-Relay-Control-for-the-Temperature-Control-Lab)", "section": "3.3.1 Relay Control for the Temperature Control Lab" } }, "source": [ "## 3.3.1 Relay Control for the Temperature Control Lab\n", "\n", "Relay control is perhaps the simplest form of feedback control that comes to mind for controlling common heaters. This is the on/off control familiar from home thermostats, air conditioners, and other devices where the manipulated variable is in either an \"on\" state or an \"off\" state.\n", "\n", "The following code implements relay control for temperature T1 on the Temperature Control Lab. At each time step $t_k$, the value of \n", "\n", "\\begin{align}\n", "U_{k} & = \\begin{cases} \n", " U^{max} &\\text{if $T_k \\leq T^{SP}_k$}\\\\\n", " U^{min} & \\text{if $T_k \\geq T^{SP}_k$}\n", " \\end{cases}\n", "\\end{align}\n", "\n", "where $ 0\\% \\leq U_{k} \\leq 100\\%$ refers to percentage of the maximum heater power, $T_k$ is the measured temperature at time $t_k$, and $T^{SP}_k$ is the temperature setpoint at time $t_k$. Typically $U^{min}$ and $U^{max}$ will be set to 0% and 100%, respectively, but other choices are possible.\n", "\n", "Relay control can be implemented as a single line of code in the standard clock-driven loop of the Temperature Control Lab." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "nbpages": { "level": 2, "link": "[3.3.1 Relay Control for the Temperature Control Lab](https://jckantor.github.io/cbe30338-2021/03.03-Relay-Control.html#3.3.1-Relay-Control-for-the-Temperature-Control-Lab)", "section": "3.3.1 Relay Control for the Temperature Control Lab" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "

" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "TCLab Model disconnected successfully.\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "%matplotlib inline\n", "from tclab import TCLab, clock, Historian, Plotter, setup\n", "\n", "TCLab = setup(connected=False, speedup=20)\n", "\n", "# control parameters\n", "U_min = 0\n", "U_max = 100\n", "T_SP = 40\n", "\n", "# time horizon and time step\n", "t_final = 250\n", "t_step = 1\n", "\n", "# perform experiment\n", "with TCLab() as lab:\n", " lab.P1 = 200\n", " h = Historian(lab.sources)\n", " p = Plotter(h, t_final)\n", " for t in clock(t_final, t_step):\n", " T1 = lab.T1 # measure temperature\n", " U1 = U_max if lab.T1 < T_SP else U_min # compute manipulated variable\n", " lab.Q1(U1) # adjust power\n", " p.update(t) # log results" ] }, { "cell_type": "markdown", "metadata": { "nbpages": { "level": 2, "link": "[3.3.2 Relay Control with Deadzone (Hysteresis) or Deadtime](https://jckantor.github.io/cbe30338-2021/03.03-Relay-Control.html#3.3.2-Relay-Control-with-Deadzone-(Hysteresis)-or-Deadtime)", "section": "3.3.2 Relay Control with Deadzone (Hysteresis) or Deadtime" } }, "source": [ "## 3.3.2 Relay Control with Deadzone (Hysteresis) or Deadtime\n", "\n", "One of the issues with simple relay control is the potential for 'chattering' where the manipulated variable (in this case heater power) exhibits periods of rapid on-and-off switching. This can be caused by systems that are highly response to control inputs, or where sensor measurements carry significant noise.\n", "\n", "There are several simple and highly effective solutions to the problem of chattering.\n", "\n", "* **Deadzone** (also called hysteresis). The manipulated variable is switched on or off only after the process variable has moved past the setpoint by a specified amount $d$.\n", "* **Deadtime** Following an on-or-off transition in the manipulated variable, no further transition is allowed for a specified period of time called the deadtime.\n", "\n", "\n", "The control algorithm for relay control with a deadzone extending $d$ above and below the setpoint, a closed form is given by\n", "\n", "\\begin{align}\n", "U_{k} & = \\begin{cases} \n", " U^{max} &\\text{if $T_k \\leq T^{SP}_k$} - d\\\\\n", " U^{min} & \\text{if $T_k \\geq T^{SP}_k$} + d\\\\\n", " U_{k-1} & \\text{ otherwise}\n", " \\end{cases}\n", "\\end{align}\n", "\n", "where $d$ is the *tolerance* or *hysteresis*. \n", "\n", "For home heating systems a typical value is in the range of 0.5 to 1 degree F. This image shows how hystersis was adjusted on a typical home thermostat in common usage in the late 20th century.\n", "\n", "\"Honeywell\n", "\n", "The furnance is turned on for temperatures below the range \n", "\n", "\\begin{align}\n", "T^{SP} - d \\leq T \\leq T^{SP} + d\n", "\\end{align}\n", "\n", "and is turned for temperatures above the range. Within the range, however, the furnance may be on or off depending on what happened at the last decision point.\n", "\n", "The following code implements relay control with hystersis. " ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "nbpages": { "level": 2, "link": "[3.3.2 Relay Control with Deadzone (Hysteresis) or Deadtime](https://jckantor.github.io/cbe30338-2021/03.03-Relay-Control.html#3.3.2-Relay-Control-with-Deadzone-(Hysteresis)-or-Deadtime)", "section": "3.3.2 Relay Control with Deadzone (Hysteresis) or Deadtime" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "TCLab Model disconnected successfully.\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "%matplotlib inline\n", "from tclab import TCLab, clock, Historian, Plotter, setup\n", "\n", "TCLab = setup(connected=False, speedup=20)\n", "\n", "# control parameters\n", "U_min = 0\n", "U_max = 100\n", "T_SP = 40\n", "d = 0.5\n", "\n", "# time horizon and time step\n", "t_final = 250\n", "t_step = 1\n", "\n", "# perform experiment\n", "with TCLab() as lab:\n", " lab.P1 = 200\n", " h = Historian(lab.sources)\n", " p = Plotter(h, t_final)\n", " U1 = U_min\n", " for t in clock(t_final, t_step):\n", " T1 = lab.T1\n", " if T1 <= T_SP - d:\n", " U1 = U_max\n", " elif T1 >= T_SP + d:\n", " U1 = U_min\n", " lab.Q1(U1)\n", " p.update(t) " ] }, { "cell_type": "markdown", "metadata": { "nbpages": { "level": 2, "link": "[3.3.2 Relay Control with Deadzone (Hysteresis) or Deadtime](https://jckantor.github.io/cbe30338-2021/03.03-Relay-Control.html#3.3.2-Relay-Control-with-Deadzone-(Hysteresis)-or-Deadtime)", "section": "3.3.2 Relay Control with Deadzone (Hysteresis) or Deadtime" } }, "source": [ "
\n", "\n", "**Study Question:** Examining the closed-loop responses, it's obvious that the heater is oversized for the purpose of control at 40 deg C. Try other values for $Q^{\\max}$ to see if you can improve closed-loop performance.\n", "\n", "**Study Question:** What is the effect of sample time on control performance? What happens if you make the controller sample time longer?\n", "\n", "**Study Question:** In a new cell, create a modification of the script to include a change in setpoint from 40 deg C to 50 deg C at the 300 second mark. Run the experiment for at least 10 minutes to see the full effect.\n", "\n", "**Study Question:** For a relay control with deadzone (also called hysteresis), try to sketch a graph of the manipulated variable $Q$ as a function of the process variable $T$. Assume the setpoint is 50 and $d = 3$. Can you draw a unique function? Why not?\n", "\n", "
" ] }, { "cell_type": "markdown", "metadata": { "nbpages": { "level": 2, "link": "[3.3.2 Relay Control with Deadzone (Hysteresis) or Deadtime](https://jckantor.github.io/cbe30338-2021/03.03-Relay-Control.html#3.3.2-Relay-Control-with-Deadzone-(Hysteresis)-or-Deadtime)", "section": "3.3.2 Relay Control with Deadzone (Hysteresis) or Deadtime" } }, "source": [ "\n", "< [3.2 Setpoints](https://jckantor.github.io/cbe30338-2021/03.02-Setpoints.html) | [Contents](toc.html) | [Tag Index](tag_index.html) | [3.4 Implementing Controllers in Python](https://jckantor.github.io/cbe30338-2021/03.04-Implementing-Controllers.html) >

\"Open

\"Download\"" ] } ], "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": "3.8.5" } }, "nbformat": 4, "nbformat_minor": 4 }