Title :
Robust static output feedback fuzzy control design for a class of nonlinear stochastic systems
Author :
Tseng, Chung-Shi ; Chen, Bor-Sen
Author_Institution :
Dept. of Electr. Eng., Ming Hsin Univ. of Sci. & Technol., Hsin-Feng, Taiwan
Abstract :
This paper describes the robust static output feedback H∞ fuzzy control design for a class of nonlinear stochastic systems. The system dynamic is modelled by Itô-type stochastic differential equations. For general nonlinear stochastic systems, the H∞ control can be obtained by solving a second-order nonlinear Hamilton-Jacobi inequality. In general, it is difficult to solve the second-order nonlinear Hamilton-Jacobi inequality. Using fuzzy approach (T-S fuzzy model), the H∞ fuzzy control design for the nonlinear stochastic systems can be given via solving linear matrix inequalities (LMIs) instead of a second-order Hamilton-Jacobi inequality. A singular value decomposition (SVD) method is proposed in this study to solve the H∞ static output feedback fuzzy control problem. By the proposed SVD method, the problem of H∞ static output feedback fuzzy control design for nonlinear stochastic systems is characterized in terms of solving an eigenvalue problem (EVP). This EVP can be easily solved by using a LMI-based optimization method. Simulation example is provided to illustrate the design procedure and the expected performances.
Keywords :
H∞ control; Jacobian matrices; control system synthesis; eigenvalues and eigenfunctions; feedback; fuzzy control; linear matrix inequalities; nonlinear control systems; nonlinear differential equations; robust control; singular value decomposition; stochastic systems; EVP; H∞ fuzzy control design; LMI; SVD method; eigenvalue problem; linear matrix inequalities; nonlinear Hamilton-Jacobi inequality; nonlinear stochastic systems; optimization method; robust control; singular value decomposition; static output feedback control; stochastic differential equations; Equations; Fuzzy control; Linear matrix inequalities; Mathematical model; Output feedback; Stochastic processes; Stochastic systems;
Conference_Titel :
Fuzzy Systems (FUZZ), 2010 IEEE International Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6919-2
DOI :
10.1109/FUZZY.2010.5584715