Trapezoid_control.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1724T006モータの台形制御の応答"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2020/2/11"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "まずはnumpyやmatplotlibモジュールのインポート\n",
    "\n",
    "そして、モータの各種諸元を設定します。\n",
    "\n",
    "PIコントローラの比例ゲインと積分ゲインをここで設定しています。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "#1724DCモータの諸元\n",
    "R=3.41\n",
    "K=6.59e-3\n",
    "L=75e-6\n",
    "D=1.4e-7\n",
    "J=1e-7\n",
    "\n",
    "#コントローラのゲイン\n",
    "Kp=0.1\n",
    "Ki=10.0\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "続いて応答を計算するための閉ループ伝達関数の分母と分子の多項式をpoly1d()を使って定義します。\n",
    "- Dcom：共通の分母\n",
    "- No:角速度の分子\n",
    "- Nu:制御入力の分子\n",
    "- Ne:誤差の分子"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {},
   "outputs": [],
   "source": [
    "#閉ループ伝達関数の分子と分母\n",
    "Dcom=np.poly1d([J*L, D*L+J*R, D*R+K**2+K*Kp, K*Ki])\n",
    "No=np.poly1d([K*Kp, K*Ki])\n",
    "Nu=np.poly1d([Kp, Ki])*np.poly1d([J*L, D*L+J*R, D*R+K**2])\n",
    "Ne=np.poly1d([J*L, D*L+J*R, D*R+K**2, 0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "極を計算します！"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {},
   "outputs": [],
   "source": [
    "#極の計算\n",
    "p=Dcom.r"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "以下では応答式の係数を求める値ごとに分けて計算しています。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {},
   "outputs": [],
   "source": [
    "#角速度の応答式係数\n",
    "ko1=No(p[0])/Dcom.deriv()(p[0])/p[0]/p[0]\n",
    "ko2=No(p[1])/Dcom.deriv()(p[1])/p[1]/p[1]\n",
    "ko3=No(p[2])/Dcom.deriv()(p[2])/p[2]/p[2]\n",
    "ko42=No(0)/Dcom(0)\n",
    "ko41=(No.deriv()(0)*Dcom(0)-No(0)*Dcom.deriv()(0))/(Dcom(0)**2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "metadata": {},
   "outputs": [],
   "source": [
    "#制御入力の応答式係数\n",
    "ku1=Nu(p[0])/Dcom.deriv()(p[0])/p[0]/p[0]\n",
    "ku2=Nu(p[1])/Dcom.deriv()(p[1])/p[1]/p[1]\n",
    "ku3=Nu(p[2])/Dcom.deriv()(p[2])/p[2]/p[2]\n",
    "ku42=Nu(0)/Dcom(0)\n",
    "ku41=(Nu.deriv()(0)*Dcom(0)-Nu(0)*Dcom.deriv()(0))/(Dcom(0)**2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {},
   "outputs": [],
   "source": [
    "#誤差の応答式係数\n",
    "ke1=Ne(p[0])/Dcom.deriv()(p[0])/p[0]/p[0]\n",
    "ke2=Ne(p[1])/Dcom.deriv()(p[1])/p[1]/p[1]\n",
    "ke3=Ne(p[2])/Dcom.deriv()(p[2])/p[2]/p[2]\n",
    "ke42=Ne(0)/Dcom(0)\n",
    "ke41=(Ne.deriv()(0)*Dcom(0)-Ne(0)*Dcom.deriv()(0))/(Dcom(0)**2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "いよいよ、応答を計算します。\n",
    "\n",
    "本記事では、まず最初に、単位ランプ応答を計算します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [],
   "source": [
    "#応答計算\n",
    "starttime=0.0\n",
    "endtime=1.0\n",
    "points=1000000\n",
    "\n",
    "t=np.linspace(starttime, endtime, points)\n",
    "\n",
    "omega1=ko1*np.exp(p[0]*t) + ko2*np.exp(p[1]*t) + ko3*np.exp(p[2]*t) + ko42*t + ko41 \n",
    "omega1=omega1.real\n",
    "\n",
    "u1=ku1*np.exp(p[0]*t) + ku2*np.exp(p[1]*t) + ku3*np.exp(p[2]*t) + ku42*t + ku41 \n",
    "u1=u1.real\n",
    "\n",
    "e1=ke1*np.exp(p[0]*t) + ke2*np.exp(p[1]*t) + ke3*np.exp(p[2]*t) + ke42*t + ke41 \n",
    "e1=e1.real"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "適切にランプ応答を遅らせる必要があります。コードが汚くなるので、遅らせる関数を作りました。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {},
   "outputs": [],
   "source": [
    "#出力を遅らせる関数\n",
    "def shift(x, s):\n",
    "    l=len(x)\n",
    "    x=np.roll(x, s)\n",
    "    dummy_ones =np.ones(l-s)\n",
    "    dummy_zeros=np.zeros(s)\n",
    "    dummy=np.concatenate([dummy_zeros,dummy_ones],0)\n",
    "    return x*dummy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ランプ応答から台形入力に対する応答を合成するには４つのランプ応答を合成する必要があります。\n",
    "\n",
    "以下で、それをしています。\n",
    "\n",
    "また、単位ランプ応答ではなく、大きさを持ったランプ入力を計算すため、出力は適宜定数倍します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {},
   "outputs": [],
   "source": [
    "#出力を遅らせて合成\n",
    "omega2=shift(omega1,int(points/4))\n",
    "omega3=shift(omega1,int(2*points/4))\n",
    "omega4=shift(omega1,int(3*points/4))\n",
    "omega=omega1-omega2-omega3+omega4\n",
    "omega=1000*omega\n",
    "\n",
    "u2=shift(u1,int(points/4))\n",
    "u3=shift(u1,int(2*points/4))\n",
    "u4=shift(u1,int(3*points/4))\n",
    "u=u1-u2-u3+u4\n",
    "u=1000*u\n",
    "\n",
    "e2=shift(e1,int(points/4))\n",
    "e3=shift(e1,int(2*points/4))\n",
    "e4=shift(e1,int(3*points/4))\n",
    "e=e1-e2-e3+e4\n",
    "e=1000*e\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "あとは可視化です。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
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       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
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       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
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       "    this.context = undefined;\n",
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       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
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       "\n",
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       "            if (mpl.ratio != 1) {\n",
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       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.subplot(311)\n",
    "plt.plot(t, omega)\n",
    "plt.grid()\n",
    "plt.ylabel('Anguler Velocity(rad/s)')\n",
    "\n",
    "plt.subplot(312)\n",
    "plt.plot(t, u)\n",
    "plt.grid()\n",
    "plt.ylabel('Input(V)')\n",
    "\n",
    "plt.subplot(313)\n",
    "plt.plot(t, e)\n",
    "plt.grid()\n",
    "plt.ylabel('Error(rad/s)')\n",
    "plt.xlabel('Time(s)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}