Cheatsheet#

Getting Started#

  • Install python control and python control plotly

pip install control control-plotly

The python control library provides several functions for the analysis of continuous time and discrete time systems. The python control plotly library provides several function for plotting the time and frequency responses in the browser using plotly.

Python control#

System Creation#

from control import tf

sys = tf([1],[3,1])

Note

Documentation : https://python-control.readthedocs.io/en/latest/generated/control.tf.html

Pour obtenir les pôles et les zéros, nous pouvons utiliser les méthodes pole() et zero(). Il est également possible d’obtenir les informations sur l’amortissement associé à chaque pôle en utilisant la méthode damp().

print(sys.pole())
print(sys.zero())
print(sys.damp())

Closed Loop#

from control import tf, feedback

sys = tf([1],[3,1])
sys_CL = feedback(sys,1)

Note

Documentation : https://python-control.readthedocs.io/en/latest/generated/control.feedback.html

Step Information#

from control import tf, step_info

sys = tf([1],[3,1])
step_info(sys,SettlingTimeThreshold=0.05,RiseTimeLimits=(0.1, 0.9))

Damping Factor#

from control import tf, damp

sys = tf([1],[3,1])
damp(sys)

Note

Documentation : https://python-control.readthedocs.io/en/latest/generated/control.damp.html

Control Plotly#

Poles Zeros Map#

from control import tf
from control_plotly import pzmap

sys = tf([1],[2,1,1])
pzmap(sys)

Note

Documentation : https://python-control-plotly.readthedocs.io/en/latest/api/_autosummary/control_plotly.pzmap.html

Step Response#

import numpy as np
from control import tf
from control_plotly import step

sys = tf([1],[2,1,1])
t = np.arange(0,20,0.01)
step(sys,t=t) # t is optional

Note

Documentation : https://python-control-plotly.readthedocs.io/en/latest/api/_autosummary/control_plotly.step.html

Impulse Response#

import numpy as np
from control import tf
from control_plotly import impulse

sys = tf([1],[2,1,1])
t = np.arange(0,20,0.01)
impulse(sys,t=t) # t is optional

Note

Documentation : https://python-control-plotly.readthedocs.io/en/latest/api/_autosummary/control_plotly.impulse.html

Bode Diagram#

import numpy as np
from control import tf
from control_plotly import bode

sys = tf([1],[2,1,1])
w = np.logspace(-1,1,100)
bode(sys,w=w) # w is optional

Note

Documentation : https://python-control-plotly.readthedocs.io/en/latest/api/_autosummary/control_plotly.bode.html

Nichols Chart#

from control import tf
from control_plotly import nichols

sys = tf([1],[2,1,1])
nichols(sys)

Note

Documentation : https://python-control-plotly.readthedocs.io/en/latest/api/_autosummary/control_plotly.nichols.html

Root Locus#

import control as ctl
from control_plotly import rlocus

sys = tf([2,5,1],[1,2,3])
rlocus(sys)

Note

Documentation : https://python-control-plotly.readthedocs.io/en/latest/api/_autosummary/control_plotly.rlocus.html