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Convex Relaxation Approach to the Identification of the Wiener-Hammerstein Model
Electrical Engineering and Computer Science, Massachusetts Institute of Technology.
2008 (English)In: Proceedings of the 47th IEEE Conference on Decision and Control, 2008, 1375-1382 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, an input/output system identificationtechnique for the Wiener-Hammerstein model and its feedbackextension is proposed. In the proposed framework, the identificationof the nonlinearity is non-parametric. The identificationproblem can be formulated as a non-convex quadratic program(QP). A convex semidefinite programming (SDP) relaxation isthen formulated and solved to obtain a sub-optimal solution tothe original non-convex QP. The convex relaxation turns out tobe tight in most cases. Combined with the use of local search,high quality solutions to the Wiener-Hammerstein identificationcan frequently be found. As an application example, randomlygenerated Wiener-Hammerstein models are identified.

Place, publisher, year, edition, pages
2008. 1375-1382 p.
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-82410DOI: 10.1109/CDC.2008.4739417OAI: oai:DiVA.org:kth-82410DiVA: diva2:498212
Conference
47th IEEE Conference on Decision and Control, 2008, CDC 2008. Cancun, Mexico. Dec. 9-11, 2008
Note
QC 20120514Available from: 2012-02-11 Created: 2012-02-11 Last updated: 2012-05-14Bibliographically approved

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Sou, Kin Cheong
Control Engineering

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