The Experts below are selected from a list of 2907 Experts worldwide ranked by ideXlab platform
Chen Peng - One of the best experts on this subject based on the ideXlab platform.
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delay dependent stability analysis and synthesis of uncertain t s fuzzy systems with time varying delay
Fuzzy Sets and Systems, 2006Co-Authors: Engang Tian, Chen PengAbstract:This paper considers the delay-dependent stability analysis and controller design for uncertain T-S fuzzy system with time-varying delay. A new method is provided by introducing some free-weighting matrices and employing the lower bound of time-varying delay. Based on the Lyapunov-Krasovskii functional method, sufficient condition for the asymptotical stability of the system is obtained. By constructing the Lyapunov-Krasovskii functional appropriately, we can avoid the Supplementary Requirement that the time-derivative of time-varying delay must be smaller than one. The fuzzy state feedback gain is derived through the numerical solution of a set of linear matrix inequalities (LMIs). The upper bound of time-delay can be obtained by using convex optimization such that the system can be stabilized for all time-delays. The efficiency of our method is demonstrated by two numerical examples.
Rajan Rakkiyappan - One of the best experts on this subject based on the ideXlab platform.
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Delay-dependent robust stability analysis of uncertain stochastic neural networks with discrete interval and distributed time-varying delays
Neurocomputing, 2009Co-Authors: Pagavathigounder Balasubramaniam, Rajan RakkiyappanAbstract:This paper is concerned with stability analysis problem for uncertain stochastic neural networks with discrete interval and distributed time-varying delays. The parameter uncertainties are assumed to be norm bounded and the delay is assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. Based on the new Lyapunov-Krasovskii functional and stochastic stability theory, delay-interval dependent stability criteria are obtained in terms of linear matrix inequalities. Some numerical examples and comparisons are provided to show that the proposed results significantly improve the allowable upper and lower bounds of delays over some existing results in the literature. Furthermore, the Supplementary Requirement that the time derivative of discrete time-varying delays must be smaller than the value one is not necessary to derive the results in this paper.
Engang Tian - One of the best experts on this subject based on the ideXlab platform.
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delay dependent stability analysis and synthesis of uncertain t s fuzzy systems with time varying delay
Fuzzy Sets and Systems, 2006Co-Authors: Engang Tian, Chen PengAbstract:This paper considers the delay-dependent stability analysis and controller design for uncertain T-S fuzzy system with time-varying delay. A new method is provided by introducing some free-weighting matrices and employing the lower bound of time-varying delay. Based on the Lyapunov-Krasovskii functional method, sufficient condition for the asymptotical stability of the system is obtained. By constructing the Lyapunov-Krasovskii functional appropriately, we can avoid the Supplementary Requirement that the time-derivative of time-varying delay must be smaller than one. The fuzzy state feedback gain is derived through the numerical solution of a set of linear matrix inequalities (LMIs). The upper bound of time-delay can be obtained by using convex optimization such that the system can be stabilized for all time-delays. The efficiency of our method is demonstrated by two numerical examples.
Pagavathigounder Balasubramaniam - One of the best experts on this subject based on the ideXlab platform.
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Delay-dependent robust stability analysis of uncertain stochastic neural networks with discrete interval and distributed time-varying delays
Neurocomputing, 2009Co-Authors: Pagavathigounder Balasubramaniam, Rajan RakkiyappanAbstract:This paper is concerned with stability analysis problem for uncertain stochastic neural networks with discrete interval and distributed time-varying delays. The parameter uncertainties are assumed to be norm bounded and the delay is assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. Based on the new Lyapunov-Krasovskii functional and stochastic stability theory, delay-interval dependent stability criteria are obtained in terms of linear matrix inequalities. Some numerical examples and comparisons are provided to show that the proposed results significantly improve the allowable upper and lower bounds of delays over some existing results in the literature. Furthermore, the Supplementary Requirement that the time derivative of discrete time-varying delays must be smaller than the value one is not necessary to derive the results in this paper.
Jun-juh Yan - One of the best experts on this subject based on the ideXlab platform.
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Guaranteed cost control for uncertain non-linear systems with time-varying delays using T–S fuzzy model
International Journal of General Systems, 2009Co-Authors: Yi-you Hou, Teh-lu Liao, Jun-juh Yan, Chang-hua LienAbstract:This paper investigates the guaranteed cost control problem of uncertain non-linear systems with time-varying delays via the Takagi–Sugeno fuzzy model approach. Based on the Lyapunov–Krasovskii functional theory and the linear matrix inequality technique, a state feedback controller is proposed to stabilise the non-linear systems and minimise the guaranteed cost of the closed-loop systems. Both delay-dependent and delay-independent stability criteria are derived to guarantee the asymptotic stability of closed-loop systems. Furthermore, the Supplementary Requirement that the time-derivative of time-varying delays must be smaller than one is released for the proposed delay-dependent stability criterion. Two illustrative examples are provided to verify the validity of the results developed in this paper.
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Stability Analysis of Takagi–Sugeno Fuzzy Cellular Neural Networks With Time-Varying Delays
IEEE transactions on systems man and cybernetics. Part B Cybernetics : a publication of the IEEE Systems Man and Cybernetics Society, 2007Co-Authors: Yi-you Hou, Teh-lu Liao, Jun-juh YanAbstract:This correspondence investigates the global exponential stability problem of Takagi-Sugeno fuzzy cellular neural networks with time-varying delays (TSFDCNNs). Based on the Lyapunov-Krasovskii functional theory and linear matrix inequality technique, a less conservative delay-dependent stability criterion is derived to guarantee the exponential stability of TSFDCNNs. By constructing a Lyapunov-Krasovskii functional, the Supplementary Requirement that the time derivative of time-varying delays must be smaller than one is released in the proposed delay-dependent stability criterion. Two illustrative examples are provided to verify the effectiveness of the proposed results
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On the synchronization of neural networks containing time-varying delays and sector nonlinearity
Physics Letters A, 2006Co-Authors: Jun-juh Yan, Jui-sheng Lin, Meei-ling Hung, Teh-lu LiaoAbstract:We present a systematic design procedure for synchronization of neural networks subject to time-varying delays and sector nonlinearity in the control input. Based on the drive-response concept and the Lyapunov stability theorem, a memoryless decentralized control law is proposed which guarantees exponential synchronization even when input nonlinearity is present. The Supplementary Requirement that the time-derivative of time-varying delays must be smaller than one is released for the proposed control scheme. A four-dimensional Hopfield neural network with time-varying delays is presented as the illustrative example to demonstrate the effectiveness of the proposed synchronization scheme.
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Delay-dependent guaranteed cost control for uncertain T-S fuzzy systems with time-varying delays
2006Co-Authors: Yi-you Hou, Teh-lu Liao, Jun-juh Yan, Chang-hua LienAbstract:The problem of guaranteed cost control for uncertain Takagi-Sugeno (T-S) fuzzy systems with time-varying delays is investigated through linear matrix inequality (LMI) approach. Based on Lyapunov-Krasovskii functional theory and LMI technique, a state feedback controller is proposed to stabilize the uncertain T-S fuzzy systems and minimize the guaranteed cost of the closed-loop systems. A delay-dependent stability criterion is derived to guarantee the asymptotical stability of closed-loop systems. By constructing a novel Lyapunov functional, the Supplementary Requirement that the time-derivative of time-varying delays must be smaller than one is released for the proposed delay-dependent stability criterion. A numerical example is given to verify the validity of the results developed in this paper.
