Stabilization for T-S model based uncertain stochastic systems

  • Authors:

  • Shaosheng Zhou;Wenyan Ren;James Lam

  • Affiliations:

  • Institute of Information and Control, Department of Automation, Hangzhou Dianzi University, Hangzhou Zhejiang 310018, PR China;Institute of Information and Control, Department of Automation, Hangzhou Dianzi University, Hangzhou Zhejiang 310018, PR China;Department of Mechanical Engineering, University of Hong Kong, Hong Kong

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2011

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Abstract

This paper considers the stabilization problem of a class of uncertain Ito stochastic fuzzy systems driven by a multidimensional Wiener process. The uncertainty modeled in the systems is of the linear fractional type which includes the norm-bounded uncertainty as a special case. The objective is to design a state-feedback fuzzy controller such that the closed-loop system is robustly asymptotically stable under a stochastic setting. By using a stochastic Lyapunov approach, sufficiency conditions for the stability and stabilization of this class of systems are established based on a novel matrix decomposition technique. The derived stability conditions are then employed to design controllers which stabilize the uncertain Ito stochastic fuzzy systems. Two simulation examples are given to illustrate the effectiveness of the approaches proposed.