Robust Model Predictive Control of a Benchmark Electromechanical System
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Data
2016-04-01
Autores
Colombo Junior, Jose Roberto
Magalhaes Afonso, Rubens Junqueira
Harrop Galvao, Roberto Kawakami
Assuncao, Edvaldo [UNESP]
Título da Revista
ISSN da Revista
Título de Volume
Editor
Springer
Resumo
This paper presents an experimental investigation concerning the use of robust model predictive control (RMPC) for a two-mass-spring system. This benchmark system has been employed as a numerical simulation example in several works involving RMPC formulations, but an actual experimental implementation has never been reported. Particular care was taken to solve the optimization problem with linear matrix inequalities within a small sampling period (15 ms). A discussion concerning the discretization of the uncertain model is presented to justify the use of the exact zero-order hold method. More specifically, the resulting loss of polytopic structure was found to be negligible with the adopted sampling period. Three experimental scenarios were considered, with different ranges for the uncertain spring stiffness coefficient. In all cases, the control task was successfully accomplished, with proper satisfaction of constraints on the input voltage and spring deformation.
Descrição
Palavras-chave
Predictive control, Robust control, Constrained control, Linear matrix inequalities, Two-mass-spring system
Como citar
Journal Of Control Automation And Electrical Systems. New York: Springer, v. 27, n. 2, p. 119-131, 2016.