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Guaranteed Cost Approach for Robust Model Predictive Control of Uncertain Linear Systems

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Autor(es):
Massera, Carlos M. ; Terra, Marco H. ; Wolf, Denis F. ; IEEE
Número total de Autores: 4
Tipo de documento: Artigo Científico
Fonte: 2017 AMERICAN CONTROL CONFERENCE (ACC); v. N/A, p. 6-pg., 2017-01-01.
Resumo

In this paper we propose a constrained guaranteed cost robust model predictive controller (GCMPC) for uncertain discrete time systems. This controller was developed based on a quadratic cost functional and guarantee robustness with respect to quadratically bound uncertainties. Such a class of problems is currently intractable by Min-Max Robust Model Predictive Controllers without polytopic approximations of the uncertainties. The proposed technique is computationally more efficient then an enumeration-based approach and requires only a Quadratically Constrained Quadratic Problem (QCQP) optimization, whereas LMI-based GCMPC approaches require a Semi-Definite Programming (SDP) optimization. (AU)

Processo FAPESP: 13/24542-7 - Projeto CARINA: localização e controle
Beneficiário:Denis Fernando Wolf
Modalidade de apoio: Auxílio à Pesquisa - Regular