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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Detalles Bibliográficos
Autores: Colombo Junior, Jose Roberto, Magalhaes Afonso, Rubens Junqueira, Harrop Galvao, Roberto Kawakami, Assuncao, Edvaldo [UNESP]
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2016
País:Brasil
Institución:Universidade Estadual Paulista (UNESP)
Repositorio:Repositório Institucional da UNESP
Idioma:inglés
OAI Identifier:oai:repositorio.unesp.br:11449/161571
Acceso en línea:http://dx.doi.org/10.1007/s40313-016-0231-9
http://hdl.handle.net/11449/161571
Access Level:acceso abierto
Palabra clave:Predictive control
Robust control
Constrained control
Linear matrix inequalities
Two-mass-spring system
Descripción
Sumario: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.