Journal
IEEE TRANSACTIONS ON FUZZY SYSTEMS
Volume 19, Issue 5, Pages 831-843Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2011.2147320
Keywords
Dynamic output feedback; linear matrix inequality (LMI); model predictive control (MPC); quadratic boundedness (QB); Takagi-Sugeno (T-S) fuzzy model
Funding
- National Nature Science Foundation of China [60934007, 60874046]
- Program for New Century Excellent Talents in the University of China
- Fundamental Research Funds for the Central Universities of China [CDJZR10175501]
- Scientific Research Foundation for Returned Overseas Chinese Scholars, the State Education Ministry of China
- Innovative Talent Training Project
- Third Stage of 211 Project
- Chongqing University [S-09108]
- Nature Science Foundation of Chongqing [2008BB2049]
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This paper addresses the output feedback predictive control for a Takagi-Sugeno (T-S) fuzzy system with bounded noise. The controller optimizes an infinite-horizon objective function respecting the input and state constraints. The control law is parameterized as a dynamic output feedback that is dependent on the membership functions, and the closed-loop stability is specified by the notion of quadratic boundedness. Online algorithms that guarantee the recursive feasibility of the convex optimization problem and the convergence of the augmented state to a neighborhood of the equilibrium point are proposed in this paper. A numerical example is given to illustrate the effectiveness of the proposed output feedback controllers.
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