On Optimal Test Signal Design and Parameter Identification Schemes for Dynamic Takagi-Sugeno Fuzzy Models Using the Fisher Information Matrix
| Autor: | Matthias Himmelsbach, Andreas Kroll |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
Fuzzy-Logik
Signal design Optimal test optimal experiment design Computer science Systemidentifikation Fisher-Information Fisher information matrix Takagi-Sugeno models Fuzzy logic Theoretical Computer Science Identification (information) symbols.namesake Takagi-Sugeno-Regler Computational Theory and Mathematics Takagi sugeno Artificial Intelligence Control theory symbols nonlinear system identification Fisher information Software Optimale Versuchsplanung |
| DOI: | 10.17170/kobra-202204206047 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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