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Mathematical Problems in Engineering
Volume 2013, Article ID 963089, 13 pages
Research Article

LMI-Based Model Predictive Control for a Class of Constrained Uncertain Fuzzy Markov Jump Systems

1Research Center of Intelligent Control and Systems, Harbin Institute of Technology, Harbin, Heilongjiang 150080, China
2Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27606, USA
3Department of Engineering, Faculty of Engineering and Science, University of Agder, 4898 Grimstad, Norway

Received 8 August 2013; Accepted 27 September 2013

Academic Editor: Jun Hu

Copyright © 2013 Ting Yang and Hamid Reza Karimi. 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.


An extended model predictive control algorithm is proposed to address constrained robust model predictive control. New upper bounds on arbitrarily long time intervals are derived by introducing two external parameters, which can relax the requirements for the increments of the Lyapunov function. The main merit of this new approach compared to other well-known techniques is the reduced conservativeness. The proposed method is proved to be effective for a class of uncertain fuzzy Markov jump systems with partially unknown transition probabilities. A single pendulum example is given to illustrate the advantages and effectiveness of the proposed controller design method.