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A novel approach for robust model predictive control applied to switched linear systems through state and output feedback

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Autor(es):
Carvalho, Luis ; Costa, Marcus V. S. ; Macedo, Leonardo H. ; Fortes, Elenilson, V
Número total de Autores: 4
Tipo de documento: Artigo Científico
Fonte: JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS; v. 360, n. 2, p. 23-pg., 2022-12-29.
Resumo

This paper proposes a robust switched model-based predictive controller design for discrete linear systems with state constraints, inputs, and disturbances limited in norm. Modeled via linear matrix inequalities, the online and offline designs of the proposed control aim at minimizing the upper bound of the quadratic performance index for a horizon of infinite prediction associated with the state estimator and the switching rule, seeking to guarantee the robust stability for closed-loop systems. To this end, three theorems are formulated. To demonstrate the effectiveness of the control strategy, a comparative analysis is performed between the performance of the proposed model and a benchmark method. From the results, it is possible to conclude that the proposed method is promising in the scope of control of linear systems subject to switching, being more efficient than the benchmark for the stabilization and control of both numerical examples.(c) 2022 The Franklin Institute. Published by Elsevier Ltd. All rights reserved. (AU)

Processo FAPESP: 15/21972-6 - Otimização do planejamento e da operação de sistemas de transmissão e de distribuição de energia elétrica
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Processo FAPESP: 18/20355-1 - Otimização do planejamento da expansão e da operação de sistemas de distribuição de energia elétrica considerando restauração da carga
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