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Robust Model Predictive Control Using Linear Matrix Inequalities for the Treatment of Asymmetric Output Constraints

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Autor(es):
Matos Cavalca, Mariana Santos ; Harrop Galvao, Roberto Kawakami ; Yoneyama, Takashi
Número total de Autores: 3
Tipo de documento: Artigo Científico
Fonte: JOURNAL OF CONTROL SCIENCE AND ENGINEERING; v. 2012, p. 7-pg., 2012-01-01.
Resumo

One of the main advantages of predictive control approaches is the capability of dealing explicitly with constraints on the manipulated and output variables. However, if the predictive control formulation does not consider model uncertainties, then the constraint satisfaction may be compromised. A solution for this inconvenience is to use robust model predictive control (RMPC) strategies based on linear matrix inequalities (LMIs). However, LMI-based RMPC formulations typically consider only symmetric constraints. This paper proposes a method based on pseudoreferences to treat asymmetric output constraints in integrating SISO systems. Such technique guarantees robust constraint satisfaction and convergence of the state to the desired equilibrium point. A case study using numerical simulation indicates that satisfactory results can be achieved. (AU)

Processo FAPESP: 08/54708-6 - Controle preditivo reconfiguravel para acomodacao de falhas.
Beneficiário:Mariana Santos Matos Cavalca
Modalidade de apoio: Bolsas no Brasil - Doutorado
Processo FAPESP: 06/58850-6 - Diagnóstico, prognóstico e acomodação de falhas em sistemas dinâmicos
Beneficiário:Takashi Yoneyama
Modalidade de apoio: Auxílio à Pesquisa - Temático