Robust Model Predictive Control Using Linear Matrix Inequalities for the Treatment of Asymmetric Output Constraints. (24th October 2011)

• Record Type: Journal Article
• Authors: Cavalca, Mariana Santos Matos; Galvão, Roberto Kawakami Harrop; Yoneyama, Takashi
• Other Names: Cychowski Marcin T. Academic Editor.
• Is Part Of: Journal of control science and engineering. Volume 2012(2012)
• Publication Date: 2011-10-24
• Subjects: Control theory -- Periodicals; 629.831205
• DOI: 10.1155/2012/485784
• Languages: English
• ISSNs: 1687-5249

Abstract

Abstract : 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.