Delay Dependent H∞ Stochastic Stability Analysis for Stochastic Nonlinear Delay Hybrid Singular System

2013 ◽  
Vol 765-767 ◽  
pp. 520-523
Author(s):  
Hong Qian Lu ◽  
Xing Ping Liu ◽  
Wu Neng Zhou
Keyword(s):  
Stability Analysis ◽  
Stochastic Stability ◽  
Initial Conditions ◽  
Singular System ◽  
Linear Matrix ◽  
Stochastically Stable ◽  
Linear Matrix Inequality Approach ◽  
Stochastic Stability Analysis ◽  
Delay Dependent ◽  
Nonlinear Delay

This paper deals with the problem of stochastic stability analysis for stochastic nonlinear delay hybrid singular system in this paper. Based on linear matrix inequality approach, a delay dependent condition is proposed, which ensures the stochastic nonlinear delay hybrid singular system is stochastically stable with H performance under zero initial conditions. Finally, an example is provided to demonstrate the effectiveness of the proposed approach.

Delay-Dependent Stochastic Stability Analysis of Singular Hybrid System

2013 ◽  
Vol 765-767 ◽  
pp. 504-507
Author(s):  
Hong Qian Lu ◽  
Xing Ping Liu ◽  
Wu Neng Zhou
Keyword(s):  
Stability Analysis ◽  
Hybrid System ◽  
Stochastic Stability ◽  
Linear Matrix ◽  
Standard Wiener Process ◽  
Markovian Jumping ◽  
Stochastically Stable ◽  
Linear Matrix Inequality Approach ◽  
Stochastic Stability Analysis ◽  
Delay Dependent

The problem of Stochastic stability analysis for singular time-delay hybrid system with Markovian jumping parameters and standard Wiener process in this paper. Based on linear matrix inequality approach, a delay dependent condition is proposed, which ensures the singular hybrid system is stochastically stable.

scholarly journals RobustH∞Filtering for Uncertain Neutral Stochastic Systems with Markovian Jumping Parameters and Time Delay

2015 ◽  
Vol 2015 ◽  
pp. 1-16
Author(s):  
Yajun Li ◽  
Zhaowen Huang
Keyword(s):  
Time Delay ◽  
Stochastic Systems ◽  
Filter Design ◽  
Linear Matrix ◽  
Markovian Jumping Parameters ◽  
Markovian Jumping ◽  
Stochastically Stable ◽  
Neutral Stochastic Systems ◽  
Error System ◽  
Delay Dependent

This paper deals with the robustH∞filter design problem for a class of uncertain neutral stochastic systems with Markovian jumping parameters and time delay. Based on the Lyapunov-Krasovskii theory and generalized Finsler Lemma, a delay-dependent stability condition is proposed to ensure not only that the filter error system is robustly stochastically stable but also that a prescribedH∞performance level is satisfied for all admissible uncertainties. All obtained results are expressed in terms of linear matrix inequalities which can be easily solved by MATLAB LMI toolbox. Numerical examples are given to show that the results obtained are both less conservative and less complicated in computation.

Robust Stochastic Stability of Discrete-Time Markovian Jump Neural Networks with Leakage Delay

2014 ◽  
Vol 69 (1-2) ◽  
pp. 70-80 ◽  
Author(s):  
Mathiyalagan Kalidass ◽  
Hongye Su ◽  
Sakthivel Rathinasamy
Keyword(s):  
Neural Networks ◽  
Discrete Time ◽  
Stochastic Stability ◽  
Leakage Delay ◽  
Linear Matrix ◽  
Stability Criteria ◽  
Markovian Jumping ◽  
Weighting Matrix ◽  
The Stability ◽  
Delay Dependent

This paper presents a robust analysis approach to stochastic stability of the uncertain Markovian jumping discrete-time neural networks (MJDNNs) with time delay in the leakage term. By choosing an appropriate Lyapunov functional and using free weighting matrix technique, a set of delay dependent stability criteria are derived. The stability results are delay dependent, which depend on not only the upper bounds of time delays but also their lower bounds. The obtained stability criteria are established in terms of linear matrix inequalities (LMIs) which can be effectively solved by some standard numerical packages. Finally, some illustrative numerical examples with simulation results are provided to demonstrate applicability of the obtained results. It is shown that even if there is no leakage delay, the obtained results are less restrictive than in some recent works.

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