Constrained robust model predicted control of discrete‐time Markov jump linear systems. Issue 4 (18th February 2019)

• Record Type: Journal Article
• Authors: Lopes, Rosileide O.; Mendes, Eduardo M. A. M.; Torres, Leonardo A. B.; Palhares, Reinaldo M.
• Is Part Of: IET control theory & applications. Volume 13:Issue 4(2019)
• Page Start: 517
• Page End: 525
• Publication Date: 2019-02-18
• Subjects: predictive control -- uncertain systems -- Markov processes -- control system synthesis -- linear systems -- linear matrix inequalities -- stochastic systems -- robust control -- discrete time systems -- state feedback; multistep mode‐dependent state‐feedback control design -- discrete‐time Markov jump linear systems -- linear matrix inequality conditions -- MPC -- robust model -- model predictive control -- uncertain system -- LMI -- transition probability; Control theory -- Periodicals; Automatic control -- Periodicals; 629.8312
• DOI: 10.1049/iet-cta.2018.5543
• Languages: English
• ISSNs: 1751-8644

Abstract

Abstract : This study is concerned with the problem of designing a robust model predictive control (MPC) for a class of uncertain discrete‐time Markov jump linear systems. The main contribution is a set of linear matrix inequality (LMI) conditions obtained under new control policies for the unconstrained as well as the constrained MPC when uncertainties are present both in the system's matrices and in the transition probabilities of the modes. For the constrained MPC, hard constraints are considered over the input control and the states and results are extended to the so‐called multi‐step mode‐dependent state‐feedback control design. To illustrate the improvements obtained with the new set of LMI conditions, numerical simulations are carried out and compared with a recent reference in the literature.