Robust H#x221E; control of nonlinear stochastic systems based on Stochastic fuzzy hyperbolic model

摘要

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 mul-tivariable 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.