Based on a piecewise quadratic lyapunov function （PQLF）, this paper presents stochastic stability analysis and synthesis methods for ItO and discrete T-S fuzzy bilinear stochastic systems. Two improved stochastic st...Based on a piecewise quadratic lyapunov function （PQLF）, this paper presents stochastic stability analysis and synthesis methods for ItO and discrete T-S fuzzy bilinear stochastic systems. Two improved stochastic stability conditions have been established in terms of linear matrix inequalities （LMIs）. It is shown that the stability in the mean square for T-S fuzzy bilinear stochastic systems can be established if a PQLF can be constructed. Considering the established stability criterion, the controller can be designed by solving a set of （LMIs）, and the closed loop system is asymptotically stable in the mean square. Two illustrative examples are provided to demonstrate the effectiveness of the results proposed in this paper.展开更多
This paper introdnces some concepts of conditional stability of stochasticVolterra equations with anticipating kernel. Snfficient conditions of these types of sta-bility are established via Lyapunov funciton.
基金This work was supported in part by the National Natural Science Foundation of China under Grant 61304063, in part by the Fundamental Research Funds for the Central Universities under Grant 72103676, in part by the Science and Technology Research Foundation of Yanan under Grant 2013-KG16, in part by Yanan University under Grant YDBK2013-12, 2012SXTS07.
文摘Based on a piecewise quadratic lyapunov function （PQLF）, this paper presents stochastic stability analysis and synthesis methods for ItO and discrete T-S fuzzy bilinear stochastic systems. Two improved stochastic stability conditions have been established in terms of linear matrix inequalities （LMIs）. It is shown that the stability in the mean square for T-S fuzzy bilinear stochastic systems can be established if a PQLF can be constructed. Considering the established stability criterion, the controller can be designed by solving a set of （LMIs）, and the closed loop system is asymptotically stable in the mean square. Two illustrative examples are provided to demonstrate the effectiveness of the results proposed in this paper.
基金Supported by Natural Science Foundation of Beijing (1022004)
文摘This paper introdnces some concepts of conditional stability of stochasticVolterra equations with anticipating kernel. Snfficient conditions of these types of sta-bility are established via Lyapunov funciton.
