A robust-control-relevance perspective on model order selection

R.M.A. Herpen, van, T.A.E. Oomen, O.H. Bosgra

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

Samenvatting

High-performance robust control hinges on explicit compensation of performance-limiting system phenomena. Hereto, such phenomena need to be described with high fidelity by the model set. Clearly, this demands for a delicate mutual selection of the nominal model and the uncertainty bound. Both should have a limited complexity to enable successful controller synthesis and implementation. The aim of this paper is to investigate model order selection for robust-control-relevant identification. Therefore, it is investigated how the worst-case performance that is associated with a model set is influenced by the complexity of the nominal model and the uncertainty bound. It turns out that, using a judiciously selected uncertainty coordinate frame, worst-case performance can be made invariant for the order of the uncertainty bound. Nevertheless, dynamic uncertainty modeling may still be worthwhile when accounting for approximations that are commonly made in robust-control-relevant identification, as is analyzed in this paper as well.
Originele taal-2Engels
TitelProceedings of the 2011 American Control Conference (ACC 2011), June 29 - July 1, 2011, San Francisco
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's1224-1229
ISBN van geprinte versie978-1-4577-0080-4
StatusGepubliceerd - 2011

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  • Citeer dit

    Herpen, van, R. M. A., Oomen, T. A. E., & Bosgra, O. H. (2011). A robust-control-relevance perspective on model order selection. In Proceedings of the 2011 American Control Conference (ACC 2011), June 29 - July 1, 2011, San Francisco (blz. 1224-1229). Institute of Electrical and Electronics Engineers.