Error using Kalman function - cannot compute stabilizing Riccati solution

Please see below a snippet of my code:

sys=ss(A_ae_control,B_ae_control,C_ae_control,0);
Qn=0.0001;
Rn=0.01*eye(size(C_ae_control,1));
[kest,L,P]=kalman(sys,Qn,Rn);

I can't seem to figure out why this won't run. I keep getting the following error:

Cannot compute the stabilizing Riccati solution P for the Kalman filter.

This could be because:

* RN is singular,

* [QN NN;NN' RN] needs to be positive definite,

* The E matrix in the state equation is singular.

Any insight would be appreciated. I have attached my A, B and C matrices.

Also, is it possible to somehow create a Kalman estimator without any measurement noise (only a disturbance). I tried setting Rn to 0 but not sure why this does not work.

[enol stark]

Have you ever solved it? im getting the error now!

[鹏 戴]

I ran into the same problem, did you solve it now?

[Emir Acevedo]

I had designing a LQR controller and after an Kalman Filter. For mi satellite control, I used the same Q and R matrix in Ricatti to solve Kest. May that can fix your problem.

Regards.

[rajesh r]

Did you sort-out this problem?

I am also getting same issue.

Answer 1

[Ivo Houtzager]

Your state-space model is probably not a minimal realization, in other words not fully obervable or not fully controllable. Perform the function minreal to remove unobservable or uncontrollable states.

sys=ss(A_ae_control,B_ae_control,C_ae_control,0);
sys=minreal(sys);
Qn=0.0001;
Rn=0.01*eye(size(C_ae_control,1));
[kest,L,P]=kalman(sys,Qn,Rn);

[rajesh r]

My model is:

A = [1 0.01; 0 1];

B = [0 ; 0];

C= [1 0];

D = 0;

after minreal,

the complete A matrix is zero

[Ivo Houtzager]

You have no inputs defined, because both B and D are zero. Thus your model is fully uncontrollable. So you have review your model inputs for correctness.