I implemented a class to identify ARX models in Python. The next step is the calculation of optimal PID parameters based on LQR. Apparently a continuous time model is required and I have the following possibilites:
- transform the discrete time model to a continuous time model,
- identify a continuous time model,
- adapt the LQR approach to determine optimal PID parameters to the discrete time domain.
In Matlab the first two approaches are easily done, but I need them in Python. Does anybody know how Matlab implemented d2c
and has a reference?
There are a few options you can use
python-control
package orscipy.signal
module or useharold
(shameless plug: I'm the author).Here is an example
Currently
zoh
,foh
,tustin
,forward euler
,backward euler
is supported including undiscretizations. The documentation is found at http://harold.readthedocs.io/en/latest/index.html