{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "  1\n",
      "-----\n",
      "s + 5\n",
      "\n",
      "[-5.]\n"
     ]
    },
    {
     "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": {
      "text/plain": [
       "(array([-5.]), array([], dtype=float64))"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "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"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from scipy.signal import lsim\n",
    "import control as ctl\n",
    "from control import (TransferFunction)\n",
    "\n",
    "\n",
    "t = np.linspace(0, 5, 101)\n",
    "\n",
    "delta = 5\n",
    "G1 = TransferFunction(1, [1,delta])\n",
    "print(G1)\n",
    "\n",
    "poles_G1= ctl.pole(G1)\n",
    "print(poles_G1)\n",
    "\n",
    "\n",
    "\n",
    "plt.figure(1)\n",
    "tout, yout = ctl.step_response(G1, t, X0=0)\n",
    "plt.plot(tout, yout, 'k', linewidth=1.5, label='resposta')\n",
    "plt.legend(loc='best', shadow=True, framealpha=1)\n",
    "plt.grid(alpha=0.3)\n",
    "plt.xlabel('t')\n",
    "plt.show()\n",
    "\n",
    "plt.figure(2)\n",
    "ctl.pzmap(G1, Plot=True, grid=False, title='Pole Zero Map')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "  1\n",
      "-----\n",
      "s - 5\n",
      "\n",
      "[5.]\n"
     ]
    },
    {
     "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": {
      "text/plain": [
       "(array([5.]), array([], dtype=float64))"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "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"
    }
   ],
   "source": [
    "delta = -5\n",
    "G2 = TransferFunction(1, [1,delta])\n",
    "print(G2)\n",
    "\n",
    "poles_G2= ctl.pole(G2)\n",
    "print(poles_G2)\n",
    "\n",
    "\n",
    "\n",
    "plt.figure(3)\n",
    "tout, yout = ctl.step_response(G2, t, X0=0)\n",
    "plt.plot(tout, yout, 'k', linewidth=1.5, label='resposta')\n",
    "plt.legend(loc='best', shadow=True, framealpha=1)\n",
    "plt.grid(alpha=0.3)\n",
    "plt.xlabel('t')\n",
    "plt.show()\n",
    "\n",
    "plt.figure(4)\n",
    "ctl.pzmap(G2, Plot=True, grid=False, title='Pole Zero Map')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "    2 s + 10\n",
      "---------------\n",
      "s^2 + 10 s + 50\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Maira\\anaconda3\\lib\\site-packages\\control\\xferfcn.py:919: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  den[j, :maxindex+1] = poly(poles[j])\n",
      "C:\\Users\\Maira\\anaconda3\\lib\\site-packages\\control\\xferfcn.py:935: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  num[i, j, maxindex+1-len(numpoly):maxindex+1] = numpoly\n"
     ]
    },
    {
     "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": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Maira\\anaconda3\\lib\\site-packages\\control\\xferfcn.py:919: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  den[j, :maxindex+1] = poly(poles[j])\n",
      "C:\\Users\\Maira\\anaconda3\\lib\\site-packages\\control\\xferfcn.py:935: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  num[i, j, maxindex+1-len(numpoly):maxindex+1] = numpoly\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(array([-5.+5.j, -5.-5.j]), array([-5.+0.j]))"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "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"
    }
   ],
   "source": [
    "delta = 5\n",
    "omega = 5\n",
    "k1 = 1\n",
    "k2 = 1\n",
    "G_ = TransferFunction(1, [1,delta-omega*1j])\n",
    "G = TransferFunction(1, [1,delta+omega*1j])\n",
    "G3 = ctl.parallel(G_,G)\n",
    "\n",
    "poles_G3= ctl.pole(G3)\n",
    "print(G3)\n",
    "\n",
    "\n",
    "\n",
    "plt.figure(5)\n",
    "tout, yout = ctl.step_response(G3, t, X0=0)\n",
    "plt.plot(tout, yout, 'k', linewidth=1.5, label='resposta')\n",
    "plt.legend(loc='best', shadow=True, framealpha=1)\n",
    "plt.grid(alpha=0.3)\n",
    "plt.xlabel('t')\n",
    "plt.show()\n",
    "\n",
    "plt.figure(6)\n",
    "ctl.pzmap(G3, Plot=True, grid=False, title='Pole Zero Map')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "    2 s - 10\n",
      "---------------\n",
      "s^2 - 10 s + 50\n",
      "\n"
     ]
    },
    {
     "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": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Maira\\anaconda3\\lib\\site-packages\\control\\xferfcn.py:919: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  den[j, :maxindex+1] = poly(poles[j])\n",
      "C:\\Users\\Maira\\anaconda3\\lib\\site-packages\\control\\xferfcn.py:935: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  num[i, j, maxindex+1-len(numpoly):maxindex+1] = numpoly\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(array([5.+5.j, 5.-5.j]), array([5.-0.j]))"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "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"
    }
   ],
   "source": [
    "delta = -5\n",
    "omega = 5\n",
    "k1 = 1\n",
    "k2 = 1\n",
    "G_ = TransferFunction(1, [1,delta-omega*1j])\n",
    "G = TransferFunction(1, [1,delta+omega*1j])\n",
    "G4 = ctl.parallel(G_,G)\n",
    "\n",
    "poles_G4= ctl.pole(G4)\n",
    "print(G4)\n",
    "\n",
    "\n",
    "\n",
    "plt.figure(7)\n",
    "tout, yout = ctl.step_response(G4, t, X0=0)\n",
    "plt.plot(tout, yout, 'k', linewidth=1.5, label='resposta')\n",
    "plt.legend(loc='best', shadow=True, framealpha=1)\n",
    "plt.grid(alpha=0.3)\n",
    "plt.xlabel('t')\n",
    "plt.show()\n",
    "\n",
    "plt.figure(8)\n",
    "ctl.pzmap(G4, Plot=True, grid=False, title='Pole Zero Map')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "  2 s\n",
      "--------\n",
      "s^2 + 25\n",
      "\n"
     ]
    },
    {
     "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": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Maira\\anaconda3\\lib\\site-packages\\control\\xferfcn.py:919: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  den[j, :maxindex+1] = poly(poles[j])\n",
      "C:\\Users\\Maira\\anaconda3\\lib\\site-packages\\control\\xferfcn.py:935: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  num[i, j, maxindex+1-len(numpoly):maxindex+1] = numpoly\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(array([-1.11022302e-16+5.j, -1.11022302e-16-5.j]), array([0.]))"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "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"
    }
   ],
   "source": [
    "delta = 0\n",
    "omega = 5\n",
    "k1 = 1\n",
    "k2 = 1\n",
    "G_ = TransferFunction(1, [1,delta-omega*1j])\n",
    "G = TransferFunction(1, [1,delta+omega*1j])\n",
    "G5 = ctl.parallel(G_,G)\n",
    "\n",
    "poles_G5= ctl.pole(G5)\n",
    "print(G5)\n",
    "\n",
    "\n",
    "\n",
    "plt.figure(9)\n",
    "tout, yout = ctl.step_response(G5, t, X0=0)\n",
    "plt.plot(tout, yout, 'k', linewidth=1.5, label='resposta')\n",
    "plt.legend(loc='best', shadow=True, framealpha=1)\n",
    "plt.grid(alpha=0.3)\n",
    "plt.xlabel('t')\n",
    "plt.show()\n",
    "\n",
    "plt.figure(10)\n",
    "ctl.pzmap(G5, Plot=True, grid=False, title='Pole Zero Map')"
   ]
  }
 ],
 "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}