Robust Model Predictive Control of a Benchmark Electromechanical System

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 implementati...

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Detalhes bibliográficos
Autores: Colombo Junior, Jose Roberto, Magalhaes Afonso, Rubens Junqueira, Harrop Galvao, Roberto Kawakami, Assuncao, Edvaldo [UNESP]
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2016
País:Brasil
Recursos:Universidade Estadual Paulista (UNESP)
Repositório:Repositório Institucional da UNESP
Idioma:inglês
OAI Identifier:oai:repositorio.unesp.br:11449/161571
Acesso em linha:http://dx.doi.org/10.1007/s40313-016-0231-9
http://hdl.handle.net/11449/161571
Access Level:Acceso aberto
Palavra-chave:Predictive control
Robust control
Constrained control
Linear matrix inequalities
Two-mass-spring system
Descrição
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.