System Identification Toolbox: How can we modify the starting parameters for the armax-algorithm?

1 Ansicht (letzte 30 Tage)
One can calculate ARMA-coefficients using the armax-algorithm from the Systems Identification Toolbox:
estimatedPolymodel=armax(iddata(outputdata,inputdata,tsample),[na nb nc nk], opt);
ARcoeff=estimatedPolymodel.A
MAcoeff=estimatedPolymodel.B
How can we modify the starting parameters for the algorithm (to accelerate and improve the results)?

Akzeptierte Antwort

Rajiv Singh
Rajiv Singh am 15 Jun. 2020
You can set the A, B, C values explicitly, as in
estimatedPolymodel.A = ARCoeff
Or, call the IDPOLY constructor with A, B, C polynomials initialized to the desired values.
A = [1 .1]
B = [0 0 4 1]
C = [1 .3]
m = idpoly(A,B,C,'Ts',1)
% refine model's initial parameter values
m2 = armax(data, m)
% but I wanted to update only A and B but not C!
m.Structure.C.Free = false;
m3 = armax(data, m)
  2 Kommentare
Urs Hackstein
Urs Hackstein am 10 Aug. 2020
Dear Rajiv Singh,
thank you very much for your prompt and precise answer which explains how to set fixed values as start parameters for A, B and C. But how can you define intervals of constraint for A, B or C, e.g.
?
Rajiv Singh
Rajiv Singh am 10 Aug. 2020
Look under the "structure" property. In addition to "Free", it also offers "Minimum" and "Maximum" specifications that you can set for individual coefficients.

Melden Sie sich an, um zu kommentieren.

Weitere Antworten (0)

Kategorien

Mehr zu Linear Model Identification finden Sie in Help Center und File Exchange

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by