{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--NOTEBOOK_HEADER-->\n",
    "*This notebook contains course material from [CBE30338](https://jckantor.github.io/CBE30338)\n",
    "by Jeffrey Kantor (jeff at nd.edu); the content is available [on Github](https://github.com/jckantor/CBE30338.git).\n",
    "The text is released under the [CC-BY-NC-ND-4.0 license](https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode),\n",
    "and code is released under the [MIT license](https://opensource.org/licenses/MIT).*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--NAVIGATION-->\n",
    "< [PID Control with Setpoint Weighting](http://nbviewer.jupyter.org/github/jckantor/CBE30338/blob/master/notebooks/04.02-PID_Control_with_Setpoint_Weighting.ipynb) | [Contents](toc.ipynb) | [PID Control with Anti-Reset-Windup](http://nbviewer.jupyter.org/github/jckantor/CBE30338/blob/master/notebooks/04.04-PID-Control-with-Anti--Reset--Windup.ipynb) ><p><a href=\"https://colab.research.google.com/github/jckantor/CBE30338/blob/master/notebooks/04.03-PID_Control_with_Bumpless_Transfer.ipynb\"><img align=\"left\" src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open in Colab\" title=\"Open in Google Colaboratory\"></a><p><a href=\"https://raw.githubusercontent.com/jckantor/CBE30338/master/notebooks/04.03-PID_Control_with_Bumpless_Transfer.ipynb\"><img align=\"left\" src=\"https://img.shields.io/badge/Github-Download-blue.svg\" alt=\"Download\" title=\"Download Notebook\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PID Control with Bumpless Transfer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Switching from Manual to Automatic Control\n",
    "\n",
    "The following cells simulate a common situation where a system is manually controlled to a desired steady state, then a controller turned on to maintain that state without further operator intervention. Examples include a pilot switching to autopilot of an aircraft at cruising altititude, or a car driver turning on cruise-control once at a desired highway driving speed.\n",
    "\n",
    "For this simulation we use PID control with setpoint weighting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "def PID(Kp, Ki, Kd, MV_bar=0, beta=1, gamma=0):\n",
    "    # initialize stored data\n",
    "    eD_prev = 0\n",
    "    t_prev = -100\n",
    "    I = 0\n",
    "    \n",
    "    # initial control\n",
    "    MV = MV_bar\n",
    "    \n",
    "    while True:\n",
    "        # yield MV, wait for new t, SP, PV\n",
    "        t, SP, PV = yield MV\n",
    "        \n",
    "        # PID calculations\n",
    "        P = Kp*(beta*SP - PV)\n",
    "        I = I + Ki*(SP - PV)*(t - t_prev)\n",
    "        eD = gamma*SP - PV\n",
    "        D = Kd*(eD - eD_prev)/(t - t_prev)\n",
    "        MV = MV_bar + P + I + D\n",
    "        \n",
    "        # update stored data for next iteration\n",
    "        eD_prev = eD\n",
    "        t_prev = t"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The desired setpoint is 50°C which is acheived with a power setting of approximately 50%.  We'll start out at the power setting for a period of 400 seconds, then turn on the controller."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b93df98>"
      ]
     },
     "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": [
       "<matplotlib.figure.Figure at 0x10b93df98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "from tclab import clock, setup, Historian, Plotter\n",
    "\n",
    "TCLab = setup(connected=False, speedup=10)\n",
    "\n",
    "controller = PID(2, 0.1, 2, beta=0)   # create pid control\n",
    "controller.send(None)                 # initialize\n",
    "\n",
    "tfinal = 1200\n",
    "SP = 50\n",
    "\n",
    "with TCLab() as lab:\n",
    "    h = Historian([('SP', lambda: SP), ('T1', lambda: lab.T1), ('MV', lambda: MV), ('Q1', lab.Q1)])\n",
    "    p = Plotter(h, tfinal)\n",
    "    for t in clock(tfinal, 2):\n",
    "        PV = lab.T1                            # get measurement\n",
    "        if t < 400:                            # choice between manual and auto control\n",
    "            MV = 50\n",
    "        else:\n",
    "            MV = controller.send([t, SP, PV])\n",
    "        lab.U1 = MV                            # apply \n",
    "        p.update(t)                            # update information display"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bumpless Transfer\n",
    "\n",
    "The previous simulation would be a genuine problem for most process operators. You have a controller that can do the job but there is no acceptable way to turn it on. Can you imagine if this happen each time a pilot turned on an autopilot, or a driver turn on cruise control?\n",
    "\n",
    "What we need is a property called **bumpless transfer**.  Bumpless transfer is a control feature that minimizes any disturbances encountered on the transition from manual to automatic operation.\n",
    "\n",
    "There are actually three elements bumpless transfer.\n",
    "\n",
    "1. Get the controller output to track the manipulated variable.\n",
    "2. Setpoint tracks the process variable during manual control.\n",
    "3. Start at or near a steady state."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Tracking the Manipulated Variable\n",
    "\n",
    "As we've seen in previous simulations, the output of the controller might not match the actual value applied to the process.  In the simulations this was due to controller output exceeding the physical limits of the manipulated variable. In the case of bumpless transfer, the cause is due to the manual adjustment of the manipulated variable. \n",
    "\n",
    "To address this issue, we add a new input to the controller called **tracking**. The controller will then attempt to maintain the output value of the manipulated variable equal to the tracking input. This will turn out to provide a number of useful properties."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def PID(Kp, Ki, Kd, MV_bar=0, beta=1, gamma=0):\n",
    "    # initialize stored data\n",
    "    eD_prev = 0\n",
    "    t_prev = -100\n",
    "    P = 0\n",
    "    I = 0\n",
    "    D = 0\n",
    "    \n",
    "    # initial control\n",
    "    MV = MV_bar\n",
    "    \n",
    "    while True:\n",
    "        # yield MV, wait for new t, SP, PV, TR\n",
    "        t, PV, SP, TR = yield MV\n",
    "        \n",
    "        # adjust I term so output matches tracking input\n",
    "        I = TR - MV_bar - P - D\n",
    "        \n",
    "        # PID calculations\n",
    "        P = Kp*(beta*SP - PV)\n",
    "        I = I + Ki*(SP - PV)*(t - t_prev)\n",
    "        eD = gamma*SP - PV\n",
    "        D = Kd*(eD - eD_prev)/(t - t_prev)\n",
    "        MV = MV_bar + P + I + D\n",
    "        \n",
    "        # update stored data for next iteration\n",
    "        eD_prev = eD\n",
    "        t_prev = t"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The implementation code also changes. In effect, the controller is always on, even if the input to process is under manual control. In `manual` mode, the controller is monitoring and tracking the manipulated variable, and always ready to take over when switched to automatic control."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10baedb38>"
      ]
     },
     "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": [
       "<matplotlib.figure.Figure at 0x10baedb38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "from tclab import clock, setup, Historian, Plotter\n",
    "\n",
    "TCLab = setup(connected=False, speedup=10)\n",
    "\n",
    "controller = PID(2, 0.1, 2, beta=0)   # create pid control\n",
    "controller.send(None)                 # initialize\n",
    "\n",
    "tfinal = 1200\n",
    "SP = 50\n",
    "\n",
    "with TCLab() as lab:\n",
    "    h = Historian([('SP', lambda: SP), ('T1', lambda: lab.T1), ('MV', lambda: MV), ('Q1', lab.Q1)])\n",
    "    p = Plotter(h, tfinal)\n",
    "    for t in clock(tfinal, 2):\n",
    "        PV = lab.T1                            # get measurement\n",
    "        MV = controller.send([t, PV, SP, lab.Q1()])\n",
    "        if t < 400:\n",
    "            lab.U1 = 50\n",
    "        else:\n",
    "            lab.U1 = MV                        # compute control action\n",
    "        p.update(t)                            # update information display"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Setpoint Tracking\n",
    "\n",
    "A second component of bumpless transfer is to have the setpoint track the process variable.  This is generally what we do in automotive cruise control when we push the `set` button."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AlcD7gOMz80jUhs5+Bpwz1SXLdevW5Z49e1pWczuaaD2x9WtWcM0rN816VGxgYID+/v75KFFTsNfVsdfVsdfVsdfViYiWBLKWXrLMzPcA72lsN0bI6p+yvBy4FNgGXAAMOn9sZiZaT8xLlJIktZeS65C9BtgWEVcCB4DLCtbSVib7BOV1l51lEJMkqc1UGsgyc2PT9z/EZS5mbKLLk64nJklS+3Kl/jbQvMq+lyclSVp8DGQL3GQ3APfypCRJi4OBbAEbPjLKBR+85Qn7vTwpSdLiYiBboMYLY94AXJKkxclAtsBMtJTFzX/0QkfEJElapAxkC8RkS1kYxiRJWtxmHcgi4vrMdO2weTDZzcCdKyZJ0uI3lxGyzfNWRYdqLGfx8CPD3gxckqQONmkgi4iHJjoErJn/cjrHRKNiV1/0HJ6xbpVBTJKkDjLVCFkA5wH7x9n/tZZU1CH2Hjz0hDC2fs0Kw5gkSR1oqkD2beD4zLxz7IGIeKA1JS1+w0dGj/kU5dUXPYe+ld0uZyFJUoeaKpBdABwe70BmPm/+y1n8RkaTS6+79ej2imVdjopJktThpvr43nWZOVxJJR1gZDS5d8/BY5a1uPHVLzCMSZLU4aYaIfvlSqpY5CZaY+y6y85ySQtJkjRlIMtKqljEJvo05fo1K1i7anmhqiRJ0kIyVSA7fYKlLwLIzDyhBTUtGo1LlK4xJkmSJjNVILsH+M0qCllMJrpE6RpjkiRpPFMFskOZ+ZNKKlkkJrtEaRiTJEnjmc7CsJomL1FKkqTZmDSQZeaZVRXS7sYbGfMSpSRJmg7XXJgnY2+F5CVKSZI0XVNdstQUGhP4x94KyTAmSZKmy0A2B+NdpvRWSJIkaaa8ZDkHYy9TrljW5a2QJEnSjDlCNkvDR0a9TClJkuZFy0fIIuILEXFnRNweEV+JiOfW958aEbdExD0R8c2IOK3VtcyX4SOjXPDBW45ue5lSkiTNRRWXLC/KzDMy87nAe4GP1Pd/CLg2M/8t8H8BH66gljkbG8YAL1NKkqQ5aXkgy8x9TZvHAaMRcQKwCbixvv9m4OkRsbHV9czWyGjy4IGhJ4Sxm//ohXQvdSqeJEmavUrmkEXEDcDm+uYW4CTg/sw8ArW7lEfELuBkYLCKmmZiotshGcYkSdJ8iMys7sUiLgN+B3gHcENmPqvp2G3AGzPzy2OesxXY2tju7e1dv3379ooqrtl3KLnmu4/fJLx7Cfyn53axdJFfphwaGqKnp6d0GR3BXlfHXlfHXlfHXldny5YtuzNzw3yft9JABhARjwEbgXuA4zPzSEQE8DPgnMwcnOz569atyz179rS8zoaxc8Y66dOUAwMD9Pf3ly6jI9jr6tjr6tjr6tjr6kRESwJZS6+3RcTqiHhq0/YrgJ8DDwE7gUvrhy4ABqcKY1Xz05SSJKkKrZ5Ddhxwc0SsAEaBPcDL6nPGXgNsi4grgQPAZS2uZUZGRpNLr7v1mH1+mlKSJLVCSwNZZv4UeP4Ex34InNvK15+tkdHk3j0Heezw4/PGnMAvSZJaxZX6xxg+Msql1916TBi77rKzDGOSJKllDGRNxlv0df2aFaxdtbxQRZIkqRMYyOrGC2PXXXYWa1ctd96YJElqKQMZ40/gd86YJEmqiokD2HvwkBP4JUlSMR2fOkZGkzd8fOfRbSfwS5KkqnV08hi7vMWKZV1O4JckSZXr2Dlk490w/P2XnOkEfkmSVLmOHSHbe/DQMWHM5S0kSVIpHTlCNnxklFdf/62j2510w3BJkrTwdNwImTcMlyRJC01HBTJvGC5Jkhaijglk3jBckiQtVB0xh8wbhkuSpIVs0QcybxguSZIWukUdyLxhuCRJageLNpCNF8acMyZJkhaiRRfIRkaTvQcPHbPOGBjGJEnSwrWoAtl4t0MCw5gkSVrYFlVKefjR4WPC2IplXYYxSZK04C2aEbKR0eThR4aPbns7JEmS1C4WRSAbb52xvpXdhjFJktQW2jqQTTSBf/2aFfT1dheqSpIkaWbaLpCNZi2EjYwmb/j4zmNGxcB1xiRJUvtpaSCLiB7gk8BpwKPAA8B/yMzBiDgBuAE4BThU3//Vqc558DBc/tHbnrB/xbIubnz1C5zAL0mS2k4VI2TXAn+XmRkRr69vnw+8B/hGZm6JiLOBv46IUzLzyExOvmJZF++/5ExHxSRJUttqaSDLzCHg8027vgH8cf37i4Cn1x93W0Q8CPwq8KXJzrlqGXz08rOPbvf1OnlfkiS1t6rnkF0BfDYijgeWZOaepmODwMlTnWBJhDcGlyRJi0pkZjUvFHEl8O+B84AVwK7MXNl0/NPAZzPzhjHP2wpsbWz39vau3759eyU1d7qhoSF6enpKl9ER7HV17HV17HV17HV1tmzZsjszN8z3eSsJZBHxJuB3gZdk5r76vkeAjY1Rsoj4JvCWzPzSZOdat25d7tmzZ7KHaJ4MDAzQ399fuoyOYK+rY6+rY6+rY6+rExHtGcjqI1yvpBbGHm7avw0YzMw/qU/qvxl4xlST+pctW5YnnnhiK0tW3aFDh1i+3MvDVbDX1bHX1bHX1bHX1dm9ezeZOe+T11sayCJiA/BT4DDQWDDsvsw8NSLOAf4e6AWOUFv24obxz/Q4R8iq47+4qmOvq2Ovq2Ovq2OvqxMRI5k573PwW7poV2beB/wE2JSZK+pfp9YP/xnwx5nZDbwK+KPpnrexQv/IaDXz32arUedca52v83SidnmvSJI6W5GV+uuLwm6ith4Z1C5XfiAiNmbm4GTPzUxed9N32L3vsaOLwXYtCR5+dJjVPct4+NHaDca7lgSre5ZxYOjw0dsoNY41bzeWzRgZzaPbkz12ouc1NO9v1Am12zm97+IzOTB0+AmPazx/vHpX9yzjik/snPA8DY3njq25eXvvwUNHezPVz726ZxkHhmthZqI+ruxeSteSOKb/zXU1ththqLE8ydjzTPQzjNffsY+bbN/IaPL2z9zFA/uHjlmvbqrXHmuieufz+aMVfbhGkrQwVRXIboqIJcCtwNuAk4D7G/PF6ovG7qK27MXgZCdKOBpOHjs8wgUfvIXupUsYPjI64XMaq/c3HtO8vWJZF3/+u8/ljz95O48dHpn0sZM9r6Hxh//AY4eP1km95lde9w2GDo8efdx4zx+v3ma79z3GBR+8ZbIWjfszjIzmMaNEU/3cAPsPjHDD4G0TnrehEZyma7Kfb6L65uqxwyO8+vpvTeu1x5rNc2b6/McOjrDphUMLak29vt7uo++bR4aPHN23kGqUpAIOtuKkVUzqPzkzd0XEMuBdwOnAO4AbMvNZTY+7DXhjZn55zPPHLHuxcv3zrvxUS2tWTY4m4R/fSizEXncFjIz59dC9BP7gWV0ssFJnxMnP1bHX1bHX1bnot/5dSz5l2fIRsszcVf/v4Yj4c+AeahP9N0TE0sw8EhFBbdRs1zjPvxq4urF9/Nq1edzq46Z83fFGbWYy0jGTx042mtOzbMnRUbG5ePJxtfVlHtg/dPQ133/JmQBHb7I+2ehes8lGtJqf8+gv9rOmr+8Jzx9vxK1hbC+aX+uDl25i66fuONqj6fwMEz1usn2N12zsf/JxPfyX33rWMf/7TPV84Ak3sB97fOxj5vL8B37+r0znfb0Q3PiT0hXMzf4DIxy3elXpMjqCva6OvW5/rf6U5UpgWdPaY1uBl2fmiyLiS8C2zNwWERcCb8rMc6Y65/Fr1+YLr/oMANdddtbRP26NOTyTzWsad57UOHOepnrs2OdNNd9pqjlgzY958nE9vOvlzz5mDtx49TRfOprO/Dd44pyvqX7u2766g/PP75+wj81z0prnmY2dm9YIZI0gN5OfYbLHTbZvvP3Tee2xl+Mmes54j5nL87d/boDNmzc/4VgJY4MkcPR9M9vLtgvJ/gP72yb8tjt7XR17XZ3/ecWvtd86ZBHxDGoT9ruAAO4F/mNmDkbEM4FtwPHAAeCyzPzeVOdsDmQfvfzstriN0lz/qJfix6irs9B63Xg/NsL0RB+GaEc7duxYMOF3sbPX1bHX1Vn3pJ72u2SZmfcCZ05w7IfAua18/YWia8nU99+czmOkqkz0flwM79HV3f5/rSr2ujr2uv21dB0ySZIkTc1AJkmSVJiBTJIkqTADmSRJUmEGMkmSpMIMZJIkSYUZyCRJkgozkEmSJBVmIJMkSSrMQCZJklSYgUySJKkwA5kkSVJhBjJJkqTCDGSSJEmFGcgkSZIKM5BJkiQVZiCTJEkqzEAmSZJUmIFMkiSpMAOZJElSYQYySZKkwgxkkiRJhRnIJEmSCjOQSZIkFWYgkyRJKsxAJkmSVJiBTJIkqTADmSRJUmEGMkmSpMIMZJIkSYUZyCRJkgozkEmSJBVmIJMkSSrMQCZJklSYgUySJKkwA5kkSVJhUwayiFhaRSGSJEmdajojZPdHxP8TEae1vBpJkqQONJ1A1g8sB74cEbdExO9HxKoW1yVJktQxpgxkmbkzM98APBV4H3ARcF9EfDgiXtjqAiVJkha7aU/qz8zhzPxkZvYDzwNOB77SssokSZI6xIw+ZRkRZ0TEnwNfB4aBV7ekKkmSpA4ynU9Z9kXE6yLiO8AXqAWxX8vMX83Mj87lxSPi1Pq8tHsi4pt+cECSJHWi6Sxp8VPgi8B/AT6XmUfm8fU/BFybmdsi4kLgw8C583h+SZKkBW86gexTwM+BXwF+JSKOOZiZb5nNC0fECcAm4Pz6rpuBD0TExswcnM05JUmS2tF05pBdDrwYeAx4ZJyv2ToJuL8x4paZCewCTp7DOSVJktpO1HLQJA+I+A1qoewc4K+Aj2Tmv8z5hSOeB9yQmc9q2ncb8MbM/HLTvq3A1sZ2b+/K9c+78lMAvOGMLlZ3Hztip/kzNDRET09P6TI6gr2ujr2ujr2ujr2uzpYtW3Zn5ob5Pu+Ulywz84vAFyNiNXAxcFNEPAa8NTNvncNr/xTYEBFLM/NI1K6FnkRtlKz59a8Grm5sH792bR63+jgANm8+m7Wrls+hBE1mYGCA/v7+0mV0BHtdHXtdHXtdHXvd/mayDtkB4G+B/wH8cv1r1jLzIWAncGl91wXAoPPHJElSp5lyhCwiuoDfAn4feDrwMWBTZv5sHl7/NcC2iLgSOABcNg/nlCRJaivT+ZTlbmqXET8CNOZ29UVEH0Bmfn+2L56ZP8RlLiRJUoebTiAbAtYB/yfwFqB5Fn0Cz2hBXZIkSR1jOpP6N1ZQhyRJUsea0b0sJUmSNP8MZJIkSYUZyCRJkgozkEmSJBVmIJMkSSrMQCZJklSYgUySJKkwA5kkSVJhBjJJkqTCDGSSJEmFGcgkSZIKM5BJkiQVZiCTJEkqzEAmSZJUmIFMkiSpMAOZJElSYQYySZKkwgxkkiRJhRnIJEmSCjOQSZIkFWYgkyRJKsxAJkmSVJiBTJIkqTADmSRJUmEGMkmSpMIMZJIkSYUZyCRJkgozkEmSJBVmIJMkSSrMQCZJklSYgUySJKkwA5kkSVJhBjJJkqTCDGSSJEmFGcgkSZIKa7tAllm6AkmSpPnVdoHskSOlK5AkSZpfbRfIGtavWUFfb3fpMiRJkuZsaekCZmrVMvjo5WfT19tN15IoXY4kSdKctV0gWxLB2lXLS5chSZI0b9r2kqUkSdJiYSCTJEkqrOWXLCNiEBiqfwH818z8VEScClwPrAX2Ab+Xmd+f6nz79u1jw4YNrSpXTQ4dOsTy5V4eroK9ro69ro69ro69rtT6Vpy0qjlkF2bmXWP2fQi4NjO3RcSFwIeBc6c60Zo1a7jvvvtaUaPGGBgYoL+/v3QZHcFeV8deV8deV8deVyciRlpx3iKT+iPiBGATcH59183AByJiY2YOTvbc0Uz2HjzU4goFcGDYXldl1BWPJamjVRXIboqIJcCtwNuAk4D7M/MIQGZmROwCTgYGJzvRwcNw+Udva3G5Ath/YIQbBu11FZYOj3L++elSLpLUoaoIZC/KzF0RsQx4F7V5Y+8Axg4JjPuXKCK2Alsb20tX9bH/wP5W1aomOZr2uiI5mmz/3ACruw1krTY0NMTAwEDpMjqCva6Ova7UwVacNLLCSyUR8RTgHuAU4EfA8Zl5JCIC+BlwzlRAFLLSAAAQjklEQVSXLI9fuzZ/OLi75bUKduzYwebNm0uXsag9/MgwW//qDvYf2M/2//gS19irgHNtqmOvq2OvqxMRuzNz3j9d2NIRsohYCSzLzH31XRcDOzPzoYjYCVwKbAMuAAanCmPgwrBVWt1tryVJqkKrL1meCNwcEV3ULkneC7yqfuw1wLaIuBI4AFzW4lokSZIWpJYGssy8FzhzgmM/ZBrLXEiSJC12rtQvSZJUmIFMkiSpMAOZJElSYQYySZKkwgxkkiRJhRnIJEmSCjOQSZIkFWYgkyRJKsxAJkmSVJiBTJIkqTADmSRJUmEGMkmSpMIMZJIkSYUZyCRJkgozkEmSJBVmIJMkSSrMQCZJklSYgUySJKkwA5kkSVJhBjJJkqTCDGSSJEmFLS1dgKSavQcPzejxfb3ddC2JFlUjSaqSgUxaIN786Ttn9Pj1a1ZwzSs3GcokaRHwkqXUpnbve4yHHx0uXYYkaR44QiYtIFdf9Bz6VnZP+piHHxlm61/dUVFFkqQqGMikBaRvZTdrVy0vXYYkqWJespQkSSrMQCZJklSYgUySJKkwA5lUUF9vN+vXrABqy1j09U4+oV+StDgZyKSCupYE17xyE284o8s1xSSpgxnIpMK6lgSru8MwJkkdzEAmSZJUmIFMkiSpsMoCWURcFREZEc+ub2+JiG9FxJ0R8Y2IeE5VtUianuEjozw2PMLeg4fYe/AQI6NZuiRJWpQqWak/IjYB5wC76tt9wI3Ar2XmDyLixcBNwLOrqEfS1IaPjHLBB285Zp83NJek1mj5CFlELAeuAV4LNP55fQrwUGb+ACAz/wl4Wj24SVoA7t178An7vKG5JLVGFZcs3wncmJk/btr3I2BdRJwDEBGvAFYBGyuoR5IkaUGJzNnPCYmI6zPzskmOnwu8GzgvMzMiBoGXZeZdEfEiamHtScBXgZcAb83Mz445x1Zga2O7t7d3/fbt22dds6ZvaGiInp6e0mV0hJn0+sBw8v47RwB4wxldrO5uzeXD3QeTbXePPGF/K1+zCr6vq2Ovq2Ovq7Nly5bdmblhvs871zlkm6c4/mLgl4EfRwTABmAgIl6dmX8H/Docvaz5APCDsSfIzKuBqxvb69aty/7+/jmWrekYGBjAXldjJr3ee/AQNwzeBsDmzWezdtXyltR09wMH+Jv773zC/la+ZhV8X1fHXlfHXre/KQNZRDw00SFgzWTPzcz3AO9pOtcgj4+QPSUzf1Y/9A7gi5n5z9OqWpIkaRGZzghZAOcB+8fZ/7U5vPafRsSv1mv4OvD7cziXJElS25pOIPs2cHxmPuHaRUQ8MJMXy8yNTd+/eibPlSRJWqymE8guAIYBImId8FhmHgTIzOe1sDZJkqSOMOWyF5n5CPAHEXE/8CCwv766/ksAImLSeWSSJEma3JSBLCL+AHg9tTle/wY4Hngr8N6IOB/4x5ZWKEmStMhN55LlFcCWzNzVtO/zEfF94B6alqSQJEnSzE1npf4lY8IYAJk5CAxm5lvnvSpJkqQOMp0Rsu6I6MnMoeadEbGCam69JGkCew8eatm5R0ZnfxcPSdLMTCeQbQc+FhF/kJn7ACKiD7gWuLmVxUma3Js//cSV9CVJ7Wc6I1xvBw4D90XEzoj4DvBT4Ej9mCRJkuZgyhGyzDwMXBIRpwCb6rt3epsjaWG4+qLn0Leye97O9/Ajw2z9qzvm7XySpKlN++bimfkvwL+0sBZJs9C3srutb/YtSXJSviRJUnEGMkmSpMIMZJIkSYUZyCRJkgozkEltpq+3m/VrVgCwfs0K+nrn7xOWkqQypv0pS0kLQ9eS4JpXbuLhR4fp6+2ma0mULkmSNEcGMqkNdS0Jl7qQpEXES5aSJEmFGcgkSZIKM5BJkiQVZiCTJEkqzEAmSZJUmIFMkiSpMAOZJElSYQYySZKkwgxkkiRJhRnIJEmSCjOQSZIkFWYgkyRJKsxAJkmSVJiBTJIkqTADmSRJUmFLSxcgqb3sPXiodAlzcmA42/5naBf2ujr2uv1VFsgi4irgT4DTM/OuiOgH/ozaKN0y4P/OzOurqkfS7Lz503eWLmFO9h8Y4YbB20qX0RHsdXXsdfurJJBFxCbgHGBXfTuAjwObM/POiNgI3B0R2zPzF1XUJEmStFC0PJBFxHLgGuASYMeYw2vq/10N/BxwvFVqA1df9Bz6VnaXLmNWduzYwebNZ5cuoyPY6+rY6+qsu6I1561ihOydwI2Z+ePawBhkZkbERcD2iHgE6AN+OzOHK6hH0hz1rexm7arlpcuYldXd0ba1txt7XR173f4iM1t38ohzgXcD59VD2CDwMuBu4O+BqzLzaxFxNvAZavPL/nXMObYCWxvbvb2967dv396ymvW4oaEhenp6SpfRERZSrw8MJ++/c2TSx7zhjC5Wd0dFFc2vhdTrxc5eV8deV2fLli27M3PDfJ+31YHsrcAVQGPkawPwIPAXwMWZeVrTY28D3pKZYy9rHmPdunW5Z8+eFlWsZgMDA/T395cuoyMspF7vPXiIyz86+eTgj15+dtv+a3wh9Xqxs9fVsdfViYiWBLKWrkOWme/JzKdm5sbM3AjcB/QD1wIbIuKZABHxS8ApwD2trEeSJGkhKrIOWWY+GBGvAf46IkaBAF6bmbtL1CNJklRSpYGsPkrW+P4TwCeqfH1JU+vr7Wb9mhXs3vfYMft7li1h6PAo69esoK+3PT9hKUkLlSv1SzpG15Lgmldu4kcP/eKYRWA/cMkmupYEfb3ddC1pzwn9krRQGcgkPUHXkid+hH68fZKk+eHNxSVJkgozkEmSJBVmIJMkSSrMQCZJklSYgUzSuBrLXwAudSFJLeanLCWNq7H8xcOPDrvUhSS1mIFM0oRc6kKSquElS0mSpMIMZJIkSYVFZpauYUYi4gjwQOk6OsQq4GDpIjqEva6Ova6Ova6Ova7OkzNz3qd8teMcsgcyc0PpIjpBRNxnr6thr6tjr6tjr6tjr6sTEfe14rxespQkSSrMQCZJklRYOwayq0sX0EHsdXXsdXXsdXXsdXXsdXVa0uu2m9QvSZK02LTjCJkkSdKiYiCTJEkqrK0CWUScGhG3RMQ9EfHNiDitdE3tKiJ6IuIz9V7eHhF/HxEb68dOqG//KCLuiohfbXrehMc0uYi4KiIyIp5d357w/ex7ffYiYnlEfKD+Hv1eRNxY32+/51lE9EfEtyNiZ/33wWX1/f4OmYOIeF9EDDb/vqjvn9V72Pf3xMbr9WR/H+vHW/P+zsy2+QK+CPxe/fsLga+Xrqldv4Ae4Dd5fB7h64Ev1L//CPAn9e/PBn4CLJ3qmF+T9nsT8Hf1fj27vm/C97Pv9Tn1+v8F3tf03n6K/W5JnwP4OXBGfXsjMAQ8yd8hc+7ti4ANwGDj90V9/6zew76/Z9bryf4+1rdb8v4u3owZNO0EYF/TDx3UVuzfWLq2xfAFnAX8c/37g8C6pmPfBH59qmN+Tdjb5cDXgac3/k8/2fvZ9/qcer2y3rtVY/bb7/nvdSOQvai+fQawG+j2d8i89bg5JMzqPez7e+a9HufY0b+P9e2WvL/b6ZLlScD9mXkEIGs/6S7g5KJVLR5XAJ+NiOOBJZm5p+nYIHDyZMcqq7I9vRO4MTN/3LRvsvez7/XZO4VaSHh7RHwrIr4SEedhv+ddvU8XAdsj4ifAV4HLqI2Q+Ttk/s32Pez7e+6uAD4L0Mq/ke0UyADGrtERRapYZCLiSuBU4D/Xd03WZ/83mIGIOJfasPV/H+ewfZ5/y4BnAN/PzLOoXWr4JLXbxNnveRQRS4G3Af9bZj4NOA+4vn7YXrfGbPtqz2dpnL+P0KJet1Mg+ymwof5LgIgIasl/V9Gq2lxEvAn4beDfZeajmfnz+v51TQ97GrBrsmNV1duGXgz8MvDjiBikNldhgNply4nez77XZ+8nwChwE0Bm3gH8mNr71H7Pr+cCT83MrwFk5m3A/dQuXfo7ZP5N9j6d7TFNYuzfR4BW/o1sm0CWmQ8BO4FL67suAAYzc7BYUW0uIrYCFwMvzcx9TYc+Dbyu/pizgSdTuxwx1TGNkZnvycynZubGzNwI3Af0Z+b1TPB+9r0+e5m5F/hHoB8gIp5Gbe7eV7Df863xh/6ZABHxS9QuGd+Dv0Pm3WTv09keq6z4NjTJ30do1fu79ES6mXwBz6Q2Ofoe4FvAs0rX1K5f1EZqEvgX4Pb61631YycCXwB+BHwPeHHT8yY85te0+j7I45N0J3w/+16fU4+fAXwJ+G79ff0K+92yXl9c7/MdwJ3A79b3+ztkbn29hto/3o5Qm4Df+MDVrN7Dvr9n1uvJ/j7Wn9OS97e3TpIkSSqsbS5ZSpIkLVYGMkmSpMIMZJIkSYUZyCRJkgozkEmSJBVmIJM0LyLi9vrX9yPiSNP2pyLirIi4qYIa/veI+OA4+0+PiC9GxB0RcVdE3BYRz251PVOJiC9FxMtK1yGpvKWlC5C0OGTmcwEiYiPwrcZ2k1dWUMbLgRvG2f9x4D9n5t8CRMRJwKEK6pGkaXGETFLLRcSvR8S36t9vjIi9EfGuiNgZEXfXR9CujYg7I+KbEfHUpue+qb7vOxHx+XqYGu81lgG/AuwY5/DJ1BZ/BCAzf5q1FcyJiCdFxF/WX+POiPiL+rmIiPUR8df1/XdGxJ/W958YEX8TEd+tj7j9YVMdgxFxVUTcEhE/joi3Nx07LSJurf8sNwE9TcfeHhE/aBpZfNqsmi2pLRnIJJVwPPD1zDwT+DDwD8B/z8wzqK0k/nqAiLgE+LfAuZm5CfgE8IEJzrkZuCUzh8c59k7gyxHxjxHx7og4s+nYe4EvZ+bzgedQu3Lw+vqxG6mt0H1Gvbb31fe/D7g7M08HfgN4R0Q8v+mcazLzhcDzgTdHxPr6/o/Vf85NwPup3XieiOgD3gRsqo8svhB4cMLuSVp0vGQpqYSDmfm5+vffAe7LzNvr298GXlr//uXAWcC3a/dEpgsYmeCcLwf+ZrwDmfneiLiRWnh6EfCViPj9zPxU/XnnRMQb6w9fAQxHxCpqweilTefZU//2JdTCG5n5UERsB84Dvlk/3ri5+Z6IuBd4ekT8gtpN5T9WP/aNiPhu/fEHqN1q5caI+ALwucw8OqInafEzkEkqoXn+1ggwNGa78bspgHdl5kcmO1nU0lo/8JaJHpOZD1IbYftERPyE2py2T9Vf4+WZee+Yc66a4mcYe9+55u2Jfp5x71WXmSMRcQ61APjrwDci4uLM/MoUNUhaJLxkKWkh+1vgtRHxb6A2T2zM5caG5wM/yMyD450kIl7RNC9sKXAGtRsHN17jrfX9RERfRPxS/VxfBf5T03nW1b/9B+APm/a9AvjiZD9IZh4A7qL+4Yb6Jc7T698/CTgxM7+SmX9af93xfk5Ji5SBTNKClZkfozaP60sRcQdwO7W5YmO9AvjMJKf6beCuiLgTuIPaCN1V9WN/DBwBbq8f/wdgY/3Y/0Htcub36q/fmFt2BXBG/fE7gHdnZuNy5WReBbw+Ir5DLdDdWt9/HLC9/iGBO4FlwPXTOJ+kRSIyxx1Bl6S2ERHfAzY3PjkpSe3GQCZJklSYlywlSZIKM5BJkiQVZiCTJEkqzEAmSZJUmIFMkiSpMAOZJElSYQYySZKkwgxkkiRJhf3//YP4ZJUsLssAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10bab7fd0>"
      ]
     },
     "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": [
       "<matplotlib.figure.Figure at 0x10bab7fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "from tclab import clock, setup, Historian, Plotter\n",
    "\n",
    "TCLab = setup(connected=False, speedup=10)\n",
    "\n",
    "controller = PID(2, 0.1, 2, beta=0)   # create pid control\n",
    "controller.send(None)                 # initialize\n",
    "\n",
    "tfinal = 1200\n",
    "SP = 50\n",
    "\n",
    "with TCLab() as lab:\n",
    "    h = Historian([('SP', lambda: SP), ('T1', lambda: lab.T1), ('MV', lambda: MV), ('Q1', lab.Q1)])\n",
    "    p = Plotter(h, tfinal)\n",
    "    for t in clock(tfinal, 2):\n",
    "        PV = lab.T1                            # get measurement\n",
    "        MV = controller.send([t, PV, PV, lab.Q1()])\n",
    "        if t < 400:\n",
    "            lab.U1 = 50\n",
    "        else:\n",
    "            lab.U1 = MV                        # compute control action\n",
    "        p.update(t)                            # update information display"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Steady State\n",
    "\n",
    "The final condition to assure bumpless transfer is to at or very near to a steady state. To demonsrate, we will repeat the last simulation, except execute the manual to auto transition at $t$ = 600 seconds."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b9c10f0>"
      ]
     },
     "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": [
       "<matplotlib.figure.Figure at 0x10b9c10f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "from tclab import clock, setup, Historian, Plotter\n",
    "\n",
    "TCLab = setup(connected=False, speedup=10)\n",
    "\n",
    "controller = PID(2, 0.1, 2, beta=0)   # create pid control\n",
    "controller.send(None)                 # initialize\n",
    "\n",
    "tfinal = 1200\n",
    "SP = 50\n",
    "\n",
    "with TCLab() as lab:\n",
    "    h = Historian([('SP', lambda: SP), ('T1', lambda: lab.T1), ('MV', lambda: MV), ('Q1', lab.Q1)])\n",
    "    p = Plotter(h, tfinal)\n",
    "    for t in clock(tfinal, 2):\n",
    "        PV = lab.T1                            # get measurement\n",
    "        MV = controller.send([t, PV, PV, lab.Q1()])\n",
    "        if t < 600:\n",
    "            lab.U1 = 50\n",
    "        else:\n",
    "            lab.U1 = MV                        # compute control action\n",
    "        p.update(t)                            # update information display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--NAVIGATION-->\n",
    "< [PID Control with Setpoint Weighting](http://nbviewer.jupyter.org/github/jckantor/CBE30338/blob/master/notebooks/04.02-PID_Control_with_Setpoint_Weighting.ipynb) | [Contents](toc.ipynb) | [PID Control with Anti-Reset-Windup](http://nbviewer.jupyter.org/github/jckantor/CBE30338/blob/master/notebooks/04.04-PID-Control-with-Anti--Reset--Windup.ipynb) ><p><a href=\"https://colab.research.google.com/github/jckantor/CBE30338/blob/master/notebooks/04.03-PID_Control_with_Bumpless_Transfer.ipynb\"><img align=\"left\" src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open in Colab\" title=\"Open in Google Colaboratory\"></a><p><a href=\"https://raw.githubusercontent.com/jckantor/CBE30338/master/notebooks/04.03-PID_Control_with_Bumpless_Transfer.ipynb\"><img align=\"left\" src=\"https://img.shields.io/badge/Github-Download-blue.svg\" alt=\"Download\" title=\"Download Notebook\"></a>"
   ]
  }
 ],
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