Module pid_simulation

ZieglerNichols tuning method

Returns the 'kp', 'ki' and 'kd' gains to a PID controller, using the Ziegler-Nichols tuning method, based on the reaction curve. For example (using Euler to discretize):

>>> g = TransferFunction([1], [1, 2, 3])
>>> kp, ki, kd = ZieglerNichols(g, 0.01, 10, Euler)
>>> print kp
7.25920108978
>>> print ki
11.9003296554
>>> print kd
1.10702816619

CohenCoon tuning method

Returns the 'kp', 'ki' and 'kd' gains to a PID controller, using the Cohen-Coon tuning method, based on the reaction curve. For example (using Euler to discretize):

>>> g = TransferFunction([1], [1, 2, 3])
>>> kp, ki, kd = CohenCoon(g, 0.01, 10, Euler)
>>> print kp
5.38204782425
>>> print ki
8.56051231163
>>> print kd
1.26879134141

ChienHronesReswick0 tuning method

Returns the 'kp', 'ki' and 'kd' gains to a PID controller, using the Chien-Hrones-Reswick (0%) tuning method, based on the reaction curve. For example (using Euler to discretize):

>>> g = TransferFunction([1], [1, 2, 3])
>>> kp, ki, kd = ChienHronesReswick0(g, 0.01, 10, Euler)
>>> print kp
3.62960054489
>>> print ki
5.90178950389
>>> print kd
0.553514083096

ChienHronesReswick20 tuning method

Returns the 'kp', 'ki' and 'kd' gains to a PID controller, using the Chien-Hrones-Reswick (20%) tuning method, based on the reaction curve. For example (using Euler to discretize):

>>> g = TransferFunction([1], [1, 2, 3])
>>> kp, ki, kd = ChienHronesReswick20(g, 0.01, 10, Euler)
>>> print kp
5.74686752941
>>> print ki
6.6746428913
>>> print kd
0.823813460341