Datum
2021-11-21Schlagwort
620 Ingenieurwissenschaften Optimale VersuchsplanungFisher-InformationTakagi-Sugeno-ReglerFuzzy-LogikSystemidentifikationMetadata
Zur Langanzeige
Aufsatz
On Optimal Test Signal Design and Parameter Identification Schemes for Dynamic Takagi-Sugeno Fuzzy Models Using the Fisher Information Matrix
Zusammenfassung
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.
Zitierform
In: International Journal of Fuzzy Systems (IJFS) Volume 24 / Issue 2 (2021-11-21) , S. 1012-1024 ; eissn:2199-3211Förderhinweis
Gefördert im Rahmen des Projekts DEALZitieren
@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},
journal={International Journal of Fuzzy Systems (IJFS)},
year={2021}
}
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2022-07-01T12:17:48Z 2022-07-01T12:17:48Z 2021-11-21 doi:10.17170/kobra-202204206047 http://hdl.handle.net/123456789/13977 Gefördert im Rahmen des Projekts DEAL eng Namensnennung 4.0 International http://creativecommons.org/licenses/by/4.0/ optimal experiment design Fisher information matrix Takagi-Sugeno models nonlinear system identification 620 On Optimal Test Signal Design and Parameter Identification Schemes for Dynamic Takagi-Sugeno Fuzzy Models Using the Fisher Information Matrix Aufsatz 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. open access Himmelsbach, Matthias Kroll, Andreas doi:10.1007/s40815-021-01185-9 KR3795/7-1 Optimale Versuchsplanung Fisher-Information Takagi-Sugeno-Regler Fuzzy-Logik Systemidentifikation publishedVersion eissn:2199-3211 Issue 2 International Journal of Fuzzy Systems (IJFS) 1012-1024 Volume 24 false
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