In this paper, the global asymptotic stability is investigated for a class of Cohen-Grossberg neural networks with time-varying and distributed delays. By using the Lyapunov-Krasovskii functional and equivalent descri...In this paper, the global asymptotic stability is investigated for a class of Cohen-Grossberg neural networks with time-varying and distributed delays. By using the Lyapunov-Krasovskii functional and equivalent descriptor form of the considered system, several delay-dependent sufficient conditions are obtained to guarantee the asymptotic stability of the addressed systems. These conditions are dependent on both time-varying and distributed delays and presented in terms of LMIs and therefore, the stability criteria of such systems can be checked readily by resorting to the Matlab LMI toolbox. Finally, an example is given to show the effectiveness and less conservatism of the proposed methods.展开更多
We study the problems of stability and stabilization for Takagi-Sugeno （T-S） fuzzy time-delay systems. First, by constructing a less-redundant Lyapunov-Krasovskii function and introducing a useful inequality, an inn...We study the problems of stability and stabilization for Takagi-Sugeno （T-S） fuzzy time-delay systems. First, by constructing a less-redundant Lyapunov-Krasovskii function and introducing a useful inequality, an innovative stability criterion is obtained, which gives a significant improvement on the performance. Compared with the exiting references, our result can use fewer unknown variables and get better results. Furthermore, based on the derived stability criteria, a new stabilization condition is developed, in which the controller gain and the maximum allowable delay bound can be obtained simultaneously. The conditions are all derived in the form of linear matrix inequality, which are easy to verify. Finally, numerical examples are given to show the effectiveness of the proposed methods.展开更多
基金the National Natural Science Foundation of China (No.60574006).
文摘In this paper, the global asymptotic stability is investigated for a class of Cohen-Grossberg neural networks with time-varying and distributed delays. By using the Lyapunov-Krasovskii functional and equivalent descriptor form of the considered system, several delay-dependent sufficient conditions are obtained to guarantee the asymptotic stability of the addressed systems. These conditions are dependent on both time-varying and distributed delays and presented in terms of LMIs and therefore, the stability criteria of such systems can be checked readily by resorting to the Matlab LMI toolbox. Finally, an example is given to show the effectiveness and less conservatism of the proposed methods.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 50977008, 61034005, and 61104021)the National High Technology Research and Development Program of China (Grant No. 2009AA04Z127)the National Basic Research Program of China (Grant No. 2009CB320601)
文摘We study the problems of stability and stabilization for Takagi-Sugeno （T-S） fuzzy time-delay systems. First, by constructing a less-redundant Lyapunov-Krasovskii function and introducing a useful inequality, an innovative stability criterion is obtained, which gives a significant improvement on the performance. Compared with the exiting references, our result can use fewer unknown variables and get better results. Furthermore, based on the derived stability criteria, a new stabilization condition is developed, in which the controller gain and the maximum allowable delay bound can be obtained simultaneously. The conditions are all derived in the form of linear matrix inequality, which are easy to verify. Finally, numerical examples are given to show the effectiveness of the proposed methods.
