Non-parametric identification of linear parameter-varying spatially-interconnected systems using an LS-SVM approach
Author | Liu, Qin |
Author | Mohammadpour, Javad |
Author | Toth, Roland| Meskin, Nader |
Available date | 2021-09-01T10:02:42Z |
Publication Date | 2016 |
Publication Name | Proceedings of the American Control Conference |
Resource | Scopus |
Abstract | This paper considers a general approach for the identification of partial differential equation-governed spatially-distributed systems. Spatial discretization virtually divides a system into spatially-interconnected subsystems, which allows to define the identification problem at the subsystem level. Here we focus on such a distributed identification of spatially-interconnected systems with temporal/spatial varying properties, whose dynamics can be captured by temporal/spatial linear parameter-varying (LPV) models. Inaccurate selection of the functional dependencies of the model parameters on scheduling variables may lead to bias in the identified models. Hence, we propose a non-parametric identification approach via a least-squares support vector machine (LS-SVM)-'non-parametric' estimation is in the sense that the model dependence on the scheduling variables is not explicitly parametrized. The performance of the proposed approach is evaluated on an Euler-Bernoulli beam with varying thickness. 2016 American Automatic Control Council (AACC). |
Language | en |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Subject | linear parameter varying spatially interconnected LS-SVM system |
Type | Conference Paper |
Pagination | 4592-4597 |
Volume Number | 2016-July |
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Electrical Engineering [2616 items ]