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Journal of Control Science and Engineering
Volume 2012 (2012), Article ID 485784, 7 pages
Research Article

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

1Departamento de Engenharia Elétrica, Centro de Ciências Tecnológicas, Universidade do Estado de Santa Catarina, Praça Rua Paulo Malschitzki, Zona Industrial Norte, 89.219-710 Joinville, SC, Brazil
2Divisão de Engenharia Eletrônica, Instituto Tecnológico de Aeronáutica, Praça Marechal Eduardo Gomes, 50 Vila das Acácias, 12.228-900 São José dos Campos, SP, Brazil

Received 30 June 2011; Revised 22 September 2011; Accepted 6 October 2011

Academic Editor: Marcin T. Cychowski

Copyright © 2012 Mariana Santos Matos Cavalca et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.