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control system using anaconda

conda install numpy scipy matplotlib    # if not yet installed
conda install -c conda-forge control slycot


# - demonstrate some standard MATLAB commands
# RMM, 25 May 09
import os
import matplotlib.pyplot as plt # MATLAB plotting functions
from control.matlab import * # MATLAB-like functions
# Parameters defining the system
m = 250.0 # system mass
k = 40.0 # spring constant
b = 60.0 # damping constant

# System matrices
A = [[0, 1.], [-k/m, -b/m]]
B = [[0], [1/m]]
C = [[1., 0]]
sys = ss(A, B, C, 0)

# Step response for the system
yout, T = step(sys)
plt.plot(T.T, yout.T)

# Bode plot for the system
mag, phase, om = bode(sys, logspace(-2, 2), plot=True)

# Nyquist plot for the system

# Root lcous plot for the system

if 'PYCONTROL_TEST_EXAMPLES' not in os.environ:




create transfer function

>>> # Create a MIMO transfer function object
>>> # The transfer function from the 2nd input to the 1st output is
>>> # (3s + 4) / (6s^2 + 5s + 4).
>>> num = [[[1., 2.], [3., 4.]], [[5., 6.], [7., 8.]]]
>>> den = [[[9., 8., 7.], [6., 5., 4.]], [[3., 2., 1.], [-1., -2., -3.]]]
>>> sys1 = tf(num, den)
mag, phase, omega = bode(sys1)

from scipy import signal
import matplotlib.pyplot as plt

s1 = signal.lti([1], [1, 1])
w, mag, phase = signal.bode(s1)

plt.semilogx(w, mag) # bode magnitude plot
plt.semilogx(w, phase) # bode phase plot


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