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Robust H control of nonlinear stochastic systems based on Stochastic fuzzy hyperbolic model

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4 Author(s)
Jun Yang ; Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China ; Yizhong Wang ; Qiuye Sun ; Dongsheng Yang

This paper is concerned with the problem of robust H control of nonlinear stochastic systems with time-varying interval delay. Firstly, a novel kind of fuzzy model, stochastic fuzzy hyperbolic model (SFHM), is proposed to represent a class of nonlinear stochastic systems with time-varying interval delay. The SFHM is a overall nonlinear stochastic model, which is much fitter for the nonlinear multivariable plant whose expert knowledge is difficult to find. The identification of SFHM is more convenient than that of stochastic T-S fuzzy model. Specifically, it also can be seen as a neural network model and we can learn the model parameters by the learning method of neural network. Secondly, delay-range-dependent and delay-derivative-range-dependent criteria on stability and H performance are developed for the SFHM by using new Lyapunov-Krasovskii functionals and improved free-weighting matrix technique for the SFHM case. Finally, simulation results show the validity of the proposed method.

Published in:

Control and Decision Conference (CCDC), 2011 Chinese

Date of Conference:

23-25 May 2011

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