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On Optimal Test Signal Design and Parameter Identification Schemes for Dynamic Takagi-Sugeno Fuzzy Models Using the Fisher Information Matrix

Himmelsbach, Matthias
Kroll, Andreas

This paper is concerned with the analysis of optimization procedures for optimal experiment design for locally affine Takagi-Sugeno (TS) fuzzy models based on the Fisher Information Matrix (FIM). The FIM is used to estimate the covariance matrix of a parameter estimate. It depends on the model parameters as well as the regression variables. Due to the dependency on the model parameters good initial models are required. Since the FIM is a matrix, a scalar measure of the FIM is optimized. Different measures and optimization goals are investigated in three case studies.

Sponsor
Gefördert im Rahmen des Projekts DEAL
Citation
In: International Journal of Fuzzy Systems (IJFS) Volume 24 / Issue 2 (2021-11-21) , S. 1012-1024; eissn:2199-3211
Collections
@article{doi:10.17170/kobra-202204206047,
  author    ={Himmelsbach, Matthias and Kroll, Andreas},
  title    ={On Optimal Test Signal Design and Parameter Identification Schemes for Dynamic Takagi-Sugeno Fuzzy Models Using the Fisher Information Matrix},
  keywords ={620 and Optimale Versuchsplanung and Fisher-Information and Takagi-Sugeno-Regler and Fuzzy-Logik and Systemidentifikation},
  copyright  ={http://creativecommons.org/licenses/by/4.0/},
  language ={en},
  journal  ={International Journal of Fuzzy Systems (IJFS)},
  year   ={2021-11-21}
}