Informative Input Design for Bayesian Identification of LPV Systems
This paper proposes an input design method for identification of linear-parameter-varying (LPV) systems. In particular, this paper focuses on the Bayesian estimation of LPV systems, especially the impulse responses of LPV systems at the scheduling variable of interest. The mutual information is empl...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2018-05-01
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| Series: | SICE Journal of Control, Measurement, and System Integration |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.9746/jcmsi.11.214 |
| Summary: | This paper proposes an input design method for identification of linear-parameter-varying (LPV) systems. In particular, this paper focuses on the Bayesian estimation of LPV systems, especially the impulse responses of LPV systems at the scheduling variable of interest. The mutual information is employed as a criterion, and a concrete procedure to obtain the local optimum is given. A numerical example is shown to demonstrate the effectiveness of the proposed input design. |
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| ISSN: | 1884-9970 |