Improving Linear State-Space Models with Additional Iterations
Systems and Control
2020-03-16 v1 Systems and Control
Abstract
An estimated state-space model can possibly be improved by further iterations with estimation data. This contribution specifically studies if models obtained by subspace estimation can be improved by subsequent re-estimation of the B, C, and D matrices (which involves linear estimation problems). Several tests are performed, which shows that it is generally advisable to do such further re-estimation steps using the maximum likelihood criterion. Stated more succinctly in terms of MATLAB functions, ssest generally outperforms n4sid.
Cite
@article{arxiv.2003.06304,
title = {Improving Linear State-Space Models with Additional Iterations},
author = {Suat Gumussoy and Ahmet Arda Ozdemir and Tomas McKelvey and Lennart Ljung and Mladen Gibanica and Rajiv Singh},
journal= {arXiv preprint arXiv:2003.06304},
year = {2020}
}
Comments
18th IFAC Symposium on System Identification, Stockholm, Sweden, July 9-11, 2018