Mean square exponential stability of impulsive control stochastic systems with time-varying delay

2009 ◽  
Vol 373 (3) ◽  
pp. 328-333 ◽  
Author(s):  
Liguang Xu ◽  
Daoyi Xu
Keyword(s):  
Exponential Stability ◽  
Stochastic Systems ◽  
Impulsive Control ◽  
Time Varying ◽  
Mean Square ◽  
Time Varying Delay ◽  
Mean Square Exponential Stability ◽  
Varying Delay

scholarly journals Stability Analysis and RobustH∞Control of Switched Stochastic Systems with Time-Varying Delay

2012 ◽  
Vol 2012 ◽  
pp. 1-17 ◽  
Author(s):  
Zhengrong Xiang ◽  
Guoxin Chen
Keyword(s):  
Exponential Stability ◽  
Stochastic Systems ◽  
Average Dwell Time ◽  
Linear Matrix ◽  
Time Varying ◽  
Mean Square ◽  
Time Varying Delay ◽  
Switched Stochastic Systems ◽  
Mean Square Exponential Stability ◽  
Varying Delay

The problems of mean-square exponential stability and robustH∞control of switched stochastic systems with time-varying delay are investigated in this paper. Based on the average dwell time method and Gronwall-Bellman inequality, a new mean-square exponential stability criterion of such system is derived in terms of linear matrix inequalities (LMIs). Then,H∞performance is studied and robustH∞controller is designed. Finally, a numerical example is given to illustrate the effectiveness of the proposed approach.

Mean-Square Exponential Stability of Stochastic Interval Cellular Neural Networks with Time-Varying Delay

2013 ◽  
Vol 760-762 ◽  
pp. 1742-1747
Author(s):  
Jin Fang Han
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Cellular Neural Networks ◽  
Time Varying ◽  
Mean Square ◽  
Razumikhin Theorem ◽  
Time Varying Delay ◽  
Mean Square Exponential Stability ◽  
The Mean ◽  
Varying Delay

This paper is concerned with the mean-square exponential stability analysis problem for a class of stochastic interval cellular neural networks with time-varying delay. By using the stochastic analysis approach, employing Lyapunov function and norm inequalities, several mean-square exponential stability criteria are established in terms of the formula and Razumikhin theorem to guarantee the stochastic interval delayed cellular neural networks to be mean-square exponential stable. Some recent results reported in the literatures are generalized. A kind of equivalent description for this stochastic interval cellular neural networks with time-varying delay is also given.

scholarly journals Delay-Dependent Robust Exponential Stability for Uncertain Neutral Stochastic Systems with Interval Time-Varying Delay

2012 ◽  
Vol 2012 ◽  
pp. 1-22 ◽  
Author(s):  
Weihua Mao ◽  
Feiqi Deng ◽  
Anhua Wan
Keyword(s):  
Exponential Stability ◽  
Stochastic Systems ◽  
Linear Matrix ◽  
Time Varying ◽  
Mean Square ◽  
Robust Exponential Stability ◽  
Interval Time ◽  
Time Varying Delay ◽  
Mean Square Exponential Stability ◽  
Delay Dependent

This paper discusses the mean-square exponential stability of uncertain neutral linear stochastic systems with interval time-varying delays. A new augmented Lyapunov-Krasovskii functional (LKF) has been constructed to derive improved delay-dependent robust mean-square exponential stability criteria, which are forms of linear matrix inequalities (LMIs). By free-weight matrices method, the usual restriction that the stability conditions only bear slow-varying derivative of the delay is removed. Finally, numerical examples are provided to illustrate the effectiveness of the proposed method.

Exponential stability for Markovian neutral stochastic systems with general transition probabilities and time-varying delay

2018 ◽  
Vol 41 (2) ◽  
pp. 350-365 ◽  
Author(s):  
Xin Zhang ◽  
Huashan Liu ◽  
Yiyuan Zheng ◽  
Yuqing Sun ◽  
Wuneng Zhou ◽  
...  
Keyword(s):  
Exponential Stability ◽  
Lyapunov Functions ◽  
Stochastic Systems ◽  
Transition Probabilities ◽  
Time Varying ◽  
Analysis Method ◽  
Multiple Lyapunov Functions ◽  
Time Varying Delay ◽  
Neutral Stochastic Systems ◽  
Varying Delay

This paper discusses the problem of exponential stability for Markovian neutral stochastic systems with general transition probabilities and time-varying delay. Based on non-convolution type multiple Lyapunov functions and stochastic analysis method, we obtain the conditions which are independent to any decay rate of the exponential stability for uncertain transition probabilities neutral stochastic systems with time-varying delay. Finally, two examples are presented to illustrate the effectiveness and potential of the proposed results.

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