RAS ödev1 g = tf([1,1],[1,5,6]).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: control in c:\\programdata\\anaconda3\\lib\\site-packages (0.9.0)\n",
      "Requirement already satisfied: scipy in c:\\programdata\\anaconda3\\lib\\site-packages (from control) (1.5.2)\n",
      "Requirement already satisfied: numpy in c:\\programdata\\anaconda3\\lib\\site-packages (from control) (1.19.2)\n",
      "Requirement already satisfied: matplotlib in c:\\programdata\\anaconda3\\lib\\site-packages (from control) (3.3.2)\n",
      "Requirement already satisfied: cycler>=0.10 in c:\\programdata\\anaconda3\\lib\\site-packages (from matplotlib->control) (0.10.0)\n",
      "Requirement already satisfied: python-dateutil>=2.1 in c:\\programdata\\anaconda3\\lib\\site-packages (from matplotlib->control) (2.8.1)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in c:\\programdata\\anaconda3\\lib\\site-packages (from matplotlib->control) (1.3.0)\n",
      "Requirement already satisfied: certifi>=2020.06.20 in c:\\programdata\\anaconda3\\lib\\site-packages (from matplotlib->control) (2020.6.20)\n",
      "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in c:\\programdata\\anaconda3\\lib\\site-packages (from matplotlib->control) (2.4.7)\n",
      "Requirement already satisfied: pillow>=6.2.0 in c:\\programdata\\anaconda3\\lib\\site-packages (from matplotlib->control) (8.0.1)\n",
      "Requirement already satisfied: six in c:\\programdata\\anaconda3\\lib\\site-packages (from cycler>=0.10->matplotlib->control) (1.15.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install control"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-3. -2.]\n",
      "[-1.]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(array([-3., -2.]), array([-1.]))"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from control import *\n",
    "import matplotlib.pyplot as plt\n",
    "from control.matlab import c2d\n",
    "import numpy as np\n",
    "\n",
    "g = tf([1,1],[1,5,6])\n",
    " \n",
    "t,y = step_response(g) \n",
    "plt.plot(t,y)\n",
    "plt.grid()\n",
    "plt.xlabel('t')\n",
    "plt.ylabel('y')\n",
    "plt.show()\n",
    "\n",
    "gz = c2d(g,0.1)\n",
    "t = np.arange(0,16,0.1)\n",
    "t1,y = step_response(gz,t)\n",
    "plt.step(t,y)\n",
    "\n",
    "plt.show()\n",
    "print(g.pole())\n",
    "print(g.zero())\n",
    "pzmap(g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([[-3.00000000e+00, -2.00000000e+00],\n",
       "        [-3.00000000e+00, -2.00000000e+00],\n",
       "        [-3.42178031e+00, -1.82583874e+00],\n",
       "        [-3.77434800e+00, -1.72089010e+00],\n",
       "        [-4.09708958e+00, -1.64576757e+00],\n",
       "        [-4.40270925e+00, -1.58776694e+00],\n",
       "        [-4.69713596e+00, -1.54095928e+00],\n",
       "        [-4.98366390e+00, -1.50205039e+00],\n",
       "        [-5.26432604e+00, -1.46900729e+00],\n",
       "        [-5.54046928e+00, -1.44048310e+00],\n",
       "        [-5.81303304e+00, -1.41553839e+00],\n",
       "        [-6.08269873e+00, -1.39349175e+00],\n",
       "        [-6.34997608e+00, -1.37383345e+00],\n",
       "        [-6.61525603e+00, -1.35617254e+00],\n",
       "        [-6.87884472e+00, -1.34020290e+00],\n",
       "        [-7.14098607e+00, -1.32568060e+00],\n",
       "        [-7.40187736e+00, -1.31240836e+00],\n",
       "        [-7.66168020e+00, -1.30022456e+00],\n",
       "        [-7.92052854e+00, -1.28899527e+00],\n",
       "        [-8.17853446e+00, -1.27860840e+00],\n",
       "        [-8.43579260e+00, -1.26896931e+00],\n",
       "        [-8.69238352e+00, -1.25999744e+00],\n",
       "        [-8.94837628e+00, -1.25162372e+00],\n",
       "        [-9.20383049e+00, -1.24378856e+00],\n",
       "        [-9.45879788e+00, -1.23644022e+00],\n",
       "        [-9.71332360e+00, -1.22953354e+00],\n",
       "        [-9.96744728e+00, -1.22302891e+00],\n",
       "        [-1.02212038e+01, -1.21689142e+00],\n",
       "        [-1.04746241e+01, -1.21109017e+00],\n",
       "        [-1.07277356e+01, -1.20559769e+00],\n",
       "        [-1.09805629e+01, -1.20038950e+00],\n",
       "        [-1.12331278e+01, -1.19544367e+00],\n",
       "        [-1.14854500e+01, -1.19074050e+00],\n",
       "        [-1.17375472e+01, -1.18626228e+00],\n",
       "        [-1.19894356e+01, -1.18199297e+00],\n",
       "        [-1.22411296e+01, -1.17791806e+00],\n",
       "        [-1.24926423e+01, -1.17402438e+00],\n",
       "        [-1.27439858e+01, -1.17029993e+00],\n",
       "        [-1.29951710e+01, -1.16673376e+00],\n",
       "        [-1.32462079e+01, -1.16331586e+00],\n",
       "        [-1.34971058e+01, -1.16003705e+00],\n",
       "        [-1.37478730e+01, -1.15688892e+00],\n",
       "        [-1.39985172e+01, -1.15386370e+00],\n",
       "        [-1.42490457e+01, -1.15095427e+00],\n",
       "        [-1.44994650e+01, -1.14815402e+00],\n",
       "        [-1.47497812e+01, -1.14545686e+00],\n",
       "        [-1.50000000e+01, -1.14285714e+00],\n",
       "        [-1.52501266e+01, -1.14034963e+00],\n",
       "        [-1.55001658e+01, -1.13792946e+00],\n",
       "        [-1.57501222e+01, -1.13559210e+00],\n",
       "        [-1.60000000e+01, -1.13333333e+00],\n",
       "        [-1.25317245e+02, -1.01608787e+00],\n",
       "        [-1.21733169e+03, -1.00164429e+00],\n",
       "        [-1.21373332e+04, -1.00016479e+00]]),\n",
       " array([0.00000000e+00, 0.00000000e+00, 2.47619048e-01, 4.95238095e-01,\n",
       "        7.42857143e-01, 9.90476190e-01, 1.23809524e+00, 1.48571429e+00,\n",
       "        1.73333333e+00, 1.98095238e+00, 2.22857143e+00, 2.47619048e+00,\n",
       "        2.72380952e+00, 2.97142857e+00, 3.21904762e+00, 3.46666667e+00,\n",
       "        3.71428571e+00, 3.96190476e+00, 4.20952381e+00, 4.45714286e+00,\n",
       "        4.70476190e+00, 4.95238095e+00, 5.20000000e+00, 5.44761905e+00,\n",
       "        5.69523810e+00, 5.94285714e+00, 6.19047619e+00, 6.43809524e+00,\n",
       "        6.68571429e+00, 6.93333333e+00, 7.18095238e+00, 7.42857143e+00,\n",
       "        7.67619048e+00, 7.92380952e+00, 8.17142857e+00, 8.41904762e+00,\n",
       "        8.66666667e+00, 8.91428571e+00, 9.16190476e+00, 9.40952381e+00,\n",
       "        9.65714286e+00, 9.90476190e+00, 1.01523810e+01, 1.04000000e+01,\n",
       "        1.06476190e+01, 1.08952381e+01, 1.11428571e+01, 1.13904762e+01,\n",
       "        1.16380952e+01, 1.18857143e+01, 1.21333333e+01, 1.21333333e+02,\n",
       "        1.21333333e+03, 1.21333333e+04]))"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from control import *\n",
    "import matplotlib.pyplot as plt\n",
    "from control.matlab import c2d\n",
    "import numpy as np\n",
    "\n",
    "g = tf([1,1],[1,5,6])\n",
    "\n",
    "rlocus(g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, None)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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F7iAyL5aG8YpIyivIzuDB62ZwxlGDwg4lISqre18CKXH3B4Amd3/R3T8JBNfNLyKSJDmZ6Zw5cTAjB+SFHUpCbKmK9DYEtbpiLAmkKfpcbmYXmdl0oO/cdSMih60dext4dvk2dtU0hh1KwowckMvgopzud0yAWBLIN82sH/Al4CbgfuA/kxqViEgAlpfv4d8eXsCair1hh5IQl58wkpdvPpOsjGCmMonlRsInoy93o2ncRaQPqW9qBQhs8sG+Jpg0JSLSC9U1tQAENvlgsl3z4Bvc8+LawMrrGz81EZE41O9LIKlfA6ltbOaldytobG4NrMxYpjJJ/Z+siEgn2hJIqjRhtbY6W6rqaGo5MEms3V4DwIRBwU0KGcv9+2vM7I/AL9x9ebIDEhEJynnHDOGIQQUpcSPhmu3VzHl4IWWVNQwsyOabl07m/MlD9n2+ens1ABMGB7cGYCxNWFOAd4H7zew1M5tjZkVJjktEJOkGF+Vw8viBZKb37tb8+qYWbnh4IXvqm/jaxZMYVpzDpx9ZyPMrt+/bZ9W2ajLTjdElwd3TEstcWNXufp+7nwzcDNxG5J6Qh8zsiKRHKCJymPvzW5tZV1nDXZdN5fpTxvLonFlMHFLETX94m6ro9CWDC3P40NRhgSbDmPpAzOwSM3sc+CHwPWAc8BfgqSTHJyJy2Hti8RYmDCrgg0eWApCXlcFdl02lqq6JHz23BoBPnjKW718+LdC4YklVq4HZwHfdfbq7f9/dt7n7H4F5yQ1PROTwVt/UwsINuzj9qNL91m2fNKyIS6cN57dvbGDr7npaWj3w2A6aQKIjsH7p7te7+6sdP3f3zx9K4WZ2vpmtMrM1ZnZrJ5+bmf0o+vkSMzsu1mMT7vbbk16EiEhH2/bU09jcylFDDux6vvGD46hrauErjy9h6h3PsGNvQ6CxHTSBuHsLSbr7PJqcfkJkjfVJwJVmNqnDbhcAE6KPOcDPenBsYt1xR1JPLyLSmcpoUhhYcOAMuxMGF3L86P68VraTQUXZlBRkBxpbLE1Yr5rZ3WZ2qpkd1/ZIQNkzgTXuXubujcCjRJrK2psNPOwRrwHFZjY0xmNFRFJeRXVbAuk8OVw8ZSi1jS1MHtYvyLCA2BLIycAxwP8Q6UD/HnBXAsoeDmxst70p+l4s+8RyLADRYccLzGxBRUVFzyK8/XYwizwiJ4s81JwlIgFZsmk3aQY1Dc2dfl6YE7mdLz3NOv08mWKZTDFZEyh2drUde4G62ieWYyNvut8L3AswY8aMnvUy3X77+8nCDDz4TioRObydOqGUn76wtstO8meXbycjzXhvR03AkcV2JzpmdhGRWkj7JW3/5xDL3gSMbLc9AtgS4z5ZMRwrIpLySgsjfR8VXXSQ33j6eNIM5i3byu7aJvrlBXdXfSz3gdwDfAz4HJG//C8DRieg7DeBCWY21syygCuAuR32mQtcEx2NNQvY7e7lMR6bWLfdltTTi4h0pm1xqPd21Hb6+bSRxVxz8hhaHRZu2BlkaLH1gbj7NcAud78DOIn9//qPi7s3A58Fniay5vrv3X2Zmd1oZjdGd3sKKAPWAPcBnz7YsYca00Gp30NEQlCYk8mkoUW8sqZyv/cr9zZwyx+XsK6yhikj+pGeZry1oSrQ2GJpwqqLPtea2TBgBzA2EYW7+1N0uJvd3e9p99qBz8R6rIhIX3T5jBHsbWjG3TEz3J3b5i7jmWVbueG0seRlZTBxSGGvTCBPmlkx8F1gEZHO6vuTGZSIiLzvug+8/zf7+soaHnxlHX9dUs5/nXcURwyKzL47fVQxT7y1ZV+SCUIskyl+w92r3P1PRPo+Jrr715IfmohIcv35rc1c/OOX960L0tv9Y+U2Tr/rBR6e/x7XnzKWT58+ft9nE4cUUd3QzJbd9YHFE+sorJOBMW37R6tQDycxLhGRpNtV28jSzXuoa2xJiVUJjygt5HuXTeXooUVMGrb/1CZtC0mt3lbN8OLcQOLpNoGY2a+A8cBioC1NO6AEIiIprW0lwrqmFvqHHEssRpXkMaqL9T6OjC4ktXrbXk4/alAg8cRSA5kBTIp2aIuI9Bm5WZEEkipNWAfTPz+LgQVZvLutOrAyYxnGuxQY0u1eIiIpJjvj/RpIXzC6JJ+Nuzq/XyQZYqmBDASWm9kbwL5bId39kqRFJSISgL5UAwEYXpzL4o1VgZUXSwK5PdlBiIiEoa0PpL6pNeRIEmNYcS5/W1pOa6uTFsDkirFMpvhi0qMQEQlBTmakFb+usa/UQHJoanEq9zYwqCin+wMOUZd9IGb2z+hztZntafeoNrM9SY9MRCTJ8qJNWLV9pQmrf2T47qaqum72TIwuayDufkr0uTCQSEREAlaYE5m5trq+KeRIEmNQYaTWUVkdzNK2sdwHMqCTt6vdvW/8xEXksFUUTSB76jpfrCnVFEenct9V2xhIebEM410EVADvAqujr9eZ2SIzOz6ZwYmIJFNOZhpZ6Wns6SM1kAH5kbVDdtUGcz2xJJB5wIXuPtDdS4ALgN8TmVr9p8kMTkQkmcyMotwMdtf1jQSSm5lOVkYau2p6Tw1khrs/3bbh7s8Ap7n7a0Dnq7yLiKSIopxM9vSRBGJm9M/LDKwJK5b7QHaa2S3Ao9HtjwG7zCwd6BuDp0XksFWYm8me+r7RBwLQLzczsBpVLDWQjxNZc/zPwBPAqOh76cDlSYtMRCQAQf7CDUJuZnpgN0bGciNhJZH10DuzJrHhiIgEqygngw07asIOI2GyM9MDm9srlmG8pcDNwDHAvlsb3f3MJMYlIhKIgQXZ7NgbTJ9BEHIz06nqRcN4HwFWElkH/Q5gPfBmEmMSEQlMaWE21Q3NfWZCxZzMtMCasGJJICXu/gDQ5O4vuvsngVlJjktEJBADCyL3TlTuDebu7WTLDbAJK5YE0ta7VG5mF5nZdCKd6iIiKa+0MHI3QkVA038kW0Z6Gs0tvaQTHfimmfUDvgT8GCgC/jOpUYmIBGRgQSSBVPaRfpDkT+L+vlhGYT0ZfbkbOCO54YiIBKstgfSVGkiQYhmFNZbIMN4x7ffXioQi0heU9LE+kCDF0oT1Z+AB4C/oznMR6WOyM9Lpn5fJtj31YYeScmJJIPXu/qOkRyIiEpJhxblsCWgRpiB4QOXEkkB+aGa3Ac8A++p47r4oaVGJiARoeHEu6/vI3ehNLa1kpscywPbQxZJAjgWuBs7k/SYsj26LiKS84f1zeWVNJe6OWZDjmBKvvql131rvyRZLAvkwMM7d+8YYNxGRDoYX51LT2MLuuiaK87LCDqfHWludtLRI4qtvbiEnMz2QcmNJIG8DxcD2RBUaXSb3d0RGdq0HLnf3XZ3sdz7wQyIz/97v7ndG378duIHI6ogAX3H3pxIVn4gcXoYX5wKwaVddSiaQO+et5NE3NjCwIJuK6gYy0o0vP/YOJflZlBRk8bETRpKXFcuv+56JpZ4zGFhpZk+b2dy2xyGWeyvwnLtPAJ6Lbu8nut7IT4isgDgJuNLMJrXb5f/cfVr0oeQhInEb3j+SQDanaEf6x04YyZ76Zsoqa6huaGZXbRO/fWMDdz+/hvlrdyQleUBsNZDbklDubOD06OuHgBeAWzrsMxNY4+5lAGb2aPS45UmIR0QOY201kM27UjOBjC8tYNa4AbxWtnO/93Mz0/n6hyZ1cdShi+VO9BeTUO5gdy+Pnr/czAZ1ss9wYGO77U3Aie22P2tm1wALgC911gQGYGZzgDkAo0aNSkTsItLHDMjPojA7g/dSeCTWlTNHHZBAPn/WBEb0z0tamV02YZlZtZnt6eRRbWZ7ujuxmT1rZks7ecyOMbbOhkK0DW/+GTAemAaUA9/r6iTufq+7z3D3GaWlpTEWLSKHEzNjbGk+ZZWpm0DOnzyE/nmZ+7aPGFTA9aeMTWqZXdZA3L3wUE7s7md39ZmZbTOzodHax1A676DfBIxstz0C2BI997Z257oPeBIRkUMwbmA+b67vtCEjJWRnpPOR6cN54JX1AHxj9mSyMpI7nDeYwcIHmgtcG319LZG11jt6E5hgZmPNLAu4Inoc0aTT5sPA0iTGKiKHgXGlBWyuqqOuMXUXlrpwSuRX45QR/ThpfEnSywsrgdwJnGNmq4FzotuY2TAzewrA3ZuBzwJPAyuA37v7sujx3zGzd8xsCZEZgjW9vIgcknGl+QCsS+FmrLYhyB89Ppglm5Iztqsb7r4DOKuT97cAF7bbfgo4YIiuu1+d1ABF5LAzduD7CWTSsKKQo4lP21roowYkr+O8vbBqICIivUpbAimr2BtyJPHbEV0Ua0B+MDdDKoGIiAB5WRmM6J/Lqm3VYYcSt7Yp6YcU5QRSnhKIiEjU0UOLWFHe7V0KvVb57noy0oyS6CqLyaYEIiISdfTQItZV1lDflJojsbbuqWdwUQ7pacHMKKwEIiISNWloIa0Oq7amZjPW1t31DC4KpvYBSiAiIvscPTQy+ipVm7G27qlnaL/cwMpTAhERiRrZP4/8rPSUTCCtrc7mXXUMKw6mAx2UQERE9klLMyYOLWLZltRLIOV76mlobmVMdDhyEJRARETamTqimKVbdtPU0tr9zr3I+ugd9GNLlEBEREIxfVQx9U2tKdeR3jYFi2ogIiIhmT6qGIC3NlaFGkdPra+sITsjLbCbCEEJRERkP8OLcyktzOatDak1tfv6HTWMKcknLaB7QEAJRERkP2bG9JHFLN5QFXYoPbJyazUTBhcEWqYSiIhIB9NH9aessoadNY1hhxKT3XVNbNpVt+8+lqAogYiIdDBzbH8AXi/bEXIksVkZvW9lkhKIiEi4powoJi8rnfkpkkDabnxUDUREJGSZ6WmcMGYAr65NjQSyvHwPA/KzAp0HC5RAREQ6dfL4EtZs38v26BobvdmyLXs4emghZsGNwAIlEBGRTp08fiBAr2/GqmloZuXWaqaP7B942UogIiKdmDSsiKKcDF5eXRl2KAf19qYqWlqd48cogYiI9ArpacYHjxrEC6u209rqYYfTpUXvRW54PE41EBGR3uOsiYOo3NvI25uqwg6lSwve28WRgwvol5cZeNlKICIiXTj9qFLSDJ5bsT3sUDrV3NLKwvd2cfzo4GsfoAQiItKl4rwsZowewHMre2cCWbJ5N9X1zXzgiIGhlK8EIiJyEGcdPYgV5XvYuLM27FAO8NK7FZjBB8YrgYiI9DrnTx4CwF/fKQ85kgO9vLqSKSOK6Z+fFUr5SiAiIgcxuiSfqSOLmbt4S9ih7Gd3XROLN1Zx2oRwah+gBCIi0q1Lpg5jefke1mzfG3Yo+7z4bgUtrc4HjywNLQYlEBGRblw8ZShmMPft3lML+ds75QwqzOa4UeGMwAIlEBGRbg0uyuHk8SU8tmhTr7ipsLaxmedXbef8yUMCXYGwo1ASiJkNMLO/m9nq6HOnKdTMHjSz7Wa2NJ7jRUQS5YoTRrFpVx0vrwl/apMXV1VQ39TKBZOHhhpHWDWQW4Hn3H0C8Fx0uzO/BM4/hONFRBLi3GMGk5uZznfnrQw7FJ5cUk5JfhYzxw4INY6wEshs4KHo64eASzvbyd1fAnbGe7yISKJkZ6QzuiSPpVv28J15K3EPpylrZ00jzyzfyuxpw0kPsfkKwksgg929HCD6PCjg40VEemxA9H6Ln76wljv+sjyU/pDH39pMU4vzsRNGBl52RxnJOrGZPQsM6eSjryarzC7imAPMARg1alSQRYtIH1PX1LLv9S9fXU/F3ga+f/lUsjPSAynf3fn9mxuZOrKYo4YUBlLmwSQtgbj72V19ZmbbzGyou5eb2VCgpxPNxHy8u98L3AswY8aM8IdPiEjKqtzbsN/2X5eUs6umkZ9ffTyFOcmfDfe1sp2s2lbNnR85NullxSKsJqy5wLXR19cCTwR8vIhIj1VWNx7w3qtrd3D1A2/Q0NzSyRGJdd/LZQwsyOLS6cOTXlYswkogdwLnmNlq4JzoNmY2zMyeatvJzH4LzAeOMrNNZnb9wY4XEUmWmobm/ZqwAEoLsvjaxZP4xXUnJL0Za/W2av6xcjvXnDSGnMxgmsy6k7QmrINx9x3AWZ28vwW4sN32lT05XkQkWdqar3Iz07no2CGs3FrNlt31XD5jRCDNV3c/v4aczDSumjU66WXFKpQEIiKSir714clcMnUYhTmZvL2xitk/eYX7Xirji+celdRyl23ZzROLt/Dp08fvGwnWG2gqExGRGIwuyecTJ47eV9uYOrKYS6YO456XyiirSO4ki9+Zt4p+uZl86oPjk1pOTymBiIjE6b8vPprsjDS++vjSpN1Y+PSyrbz4bgWfPeMI+uUGv+75wSiBiIjEaVBhDrdeMJH5ZTv4zRsbEn7+PfVNfP2JpUwcUsh1HxiT8PMfKiUQEZFDcOUJozh1wkD+5y/LWbl1T0LP/b9/XcH26gbu/JcpZKb3vl/XvS8iEZEUkpZmfP/yaRTmZPLpRxaxu7YpIed9/K1NPPrmRj512nimjSxOyDkTTQlEROQQlRZmc/fHp7NxZy1zfrXgkG8qXLyxiq88tpQTxw7gpnOPTFCUiacEIiKSALPGlXDXZVN5fd1OPvPIIuqb4ksi726r5rpfvEFpYTY//vh0Mnph01Wb3huZiEiKmT1tON+8dDLPrdzOtQ++wY4Oc2d15411O7nsnvlkpqfx6+tPZFBhTpIiTQwlEBGRBLpq1mh+8LFpvLWxigt++DLPr+p+rtjmllbu/sdqPnH/a5QUZPHYv5/MqJK8AKI9NLoTXUQkwWZPG86EQYV87reL+NdfvMkpRwzk2pPHcOqEgfvNY7WrppF5y7Zy70tlrKus4aIpQ/nWpZMpzus9d5sfjIW1qlYYZsyY4QsWLAg7DBE5TDQ0t/Cr+e/x85fKqKhuICs9jXGl+eRnZ7CzppH3dtTQ6jBpaBFfOHsC5x7T2RJK4TOzhe4+44D3lUBERJKrqaWVl1dX8HrZTtZW1FDb2MyA/CzGlxZwxsRBTB3RD7Nwl6c9mK4SiJqwRESSLDM9jTMnDubMiYPDDiWh1IkuIiJxUQIREZG4KIGIiEhclEBERCQuSiAiIhIXJRAREYmLEoiIiMRFCUREROKiBCIiInFRAhERkbgogYiISFyUQEREJC5KICIiEhclEBERicthtR6ImVUA78V5+ECgMoHhhKUvXIeuoffoC9fRF64Bknsdo929tOObh1UCORRmtqCzBVVSTV+4Dl1D79EXrqMvXAOEcx1qwhIRkbgogYiISFyUQGJ3b9gBJEhfuA5dQ+/RF66jL1wDhHAd6gMREZG4qAYiIiJxUQIREZG4KIF0wcwuM7NlZtZqZl0OjTOz881slZmtMbNbg4yxO2Y2wMz+bmaro8/9u9jvP6PXutTMfmtmOUHHejA9uI5iM/ujma00sxVmdlLQsXYl1muI7ptuZm+Z2ZNBxhiLWK7DzEaa2fPRf4NlZvYfYcTaUXffVYv4UfTzJWZ2XBhxHkwM1/CJaOxLzOxVM5uazHiUQLq2FPgI8FJXO5hZOvAT4AJgEnClmU0KJryY3Ao85+4TgOei2/sxs+HA54EZ7j4ZSAeuCDTK7nV7HVE/BOa5+0RgKrAioPhiEes1APwHvSv29mK5jmbgS+5+NDAL+EzY34sYv6sXABOijznAzwINshsxXsM64IPuPgX4BknuWFcC6YK7r3D3Vd3sNhNY4+5l7t4IPArMTn50MZsNPBR9/RBwaRf7ZQC5ZpYB5AFbkh9aj3R7HWZWBJwGPADg7o3uXhVQfLGI6d/CzEYAFwH3BxNWj3V7He5e7u6Loq+riSTD4UEF2IVYvquzgYc94jWg2MyGBh3oQXR7De7+qrvvim6+BoxIZkBKIIdmOLCx3fYmwv+itDfY3csh8qUGBnXcwd03A3cBG4ByYLe7PxNolN3r9jqAcUAF8Ito88/9ZpYfZJDdiOUaAH4A3Ay0BhRXT8V6HQCY2RhgOvB68kM7qFi+q739+9zT+K4H/pbMgDKSefLezsyeBYZ08tFX3f2JWE7RyXuBjos+2DXEeHx/In/FjAWqgD+Y2VXu/uuEBRlbHId0HUT+Lx8HfM7dXzezHxJpXvlagkLsVgL+LS4Gtrv7QjM7PYGh9UgC/i3azlMA/An4grvvSURshyCW72ro3+duxByfmZ1BJIGcksyADusE4u5nH+IpNgEj222PIODmn4Ndg5ltM7Oh7l4erYpv72S3s4F17l4RPeYx4GQg0ASSgOvYBGxy97a/dP/IwfsZEi4B1/AB4BIzuxDIAYrM7NfuflWSQu5UAq4DM8skkjwecffHkhRqT8TyXQ39+9yNmOIzsylEmkAvcPcdyQxITViH5k1ggpmNNbMsIp3Pc0OOqb25wLXR19cCndWqNgCzzCzPzAw4i97Xgdvtdbj7VmCjmR0VfessYHkw4cUklmv4sruPcPcxRP4v/SPo5BGDbq8j+v/oAWCFu38/wNgOJpbv6lzgmuhorFlEmnPLgw70ILq9BjMbBTwGXO3u7yY9InfXo5MH8GEiGb8B2AY8HX1/GPBUu/0uBN4F1hJp+go99naxlRAZKbM6+jygi2u4A1hJZOTZr4DssGOP8zqmAQuAJcCfgf5hx97Ta2i3/+nAk2HHHc91EGk28ei/w+Lo48JeEPsB31XgRuDG6GsjMsppLfAOkZGJof/Me3gN9wO72v3cFyQzHk1lIiIicVETloiIxEUJRERE4qIEIiIicVECERGRuCiBiIhIXJRARHrIzFrMbHF09uK/mFlxnOe5zszuTkA8l3Q2M6tIsimBiPRcnbtP88jsxTuBz4QZjLvPdfc7w4xBDk9KICKHZj7RCe3MbLyZzTOzhWb2splNjL7/ITN7PTrJ47NmNvhgJzSzmdG1HN6KPh8Vff+LZvZg9PWx0RpQXvuajEXWsVlqZm+bWZdLEYgkghKISJyi6zOcxfvTSdxLZDLH44GbgJ9G3/8nMMvdpxOZgvvmbk69Ejgtuv/Xgf+Nvv8D4Agz+zDwC+BT7l7b4divA+e5+1TgknivTSQWh/VkiiJxyjWzxcAYYCHw9+jMsycTmc24bb/s6PMI4HfRyQeziCz6czD9gIfMbAKRKUEyAdy91cyuIzJFyM/d/ZVOjn0F+KWZ/Z7InEgiSaMaiEjP1bn7NGA0kYTwGSLfpapo30jb4+jo/j8G7nb3Y4FPEZlp92C+ATwf7WP5UIf9JwB7icw9dQB3vxH4byKzti42s5J4LlAkFkogInFy991ElgO+CagD1pnZZbBvfe229aj7AZujr6894EQHar//dW1vmlk/Isv2ngaUmNlHOx5oZuPd/XV3/zpQyf7Tf4sklBKIyCFw97eAt4lMrf0J4HozextYxvvLjd5OpGnrZSK/1LvzHeDbZvYKkTXq2/wf8FOPTNN9PXCnmXVcEfC7ZvaOmS0FXorGJpIUmo1XRETiohqIiIjERQlERETiogQiIiJxUQIREZG4KIGIiEhclEBERCQuSiAiIhKX/w8QNVSDtFhGxgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from control import *\n",
    "import matplotlib.pyplot as plt\n",
    "from control.matlab import c2d\n",
    "import numpy as np\n",
    "\n",
    "g = tf([1,1],[1,5,6])\n",
    "nyquist_plot(g), plt.grid()"
   ]
  },
  {
   "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}