Hello all,
I have a double about the idgrey() function for system identification of linear system.
It is clear that we can either use continuous-time or discrete-time state space description by using idgrey().
The two (continous-time or discrete-time) have different matrix A,B,C,D. for the same dymamic system.
Now, I start with a continous-time state space with idgrey() with 'c' as continous parameter. I can't define the parameter sampling time T>0: this is normal.
My question is: if I use 'cd' as continous-discrete time parameter, and I can assign the sampling time T>0, which kind of state-space description I will get?
Is it a continous-time description with a positive sampling time? as we use the function c2d()?
2.
My intention is to estimate a linear grey-box model with continous-time description, but I have only the sampling data in discrete time.
How can I realize the system identification effectively?
One way, I am using now is idgrey() + idss() + c2d() and then greyest().
is this way correct?
Best Answer