A New Delay-dependent Absolute Stability Criterion for Lurie Systems with Time-varying delay

Delay-dependent robust stability criteria of uncertain stochastic systems with time-varying delay

This paper is concerned with the problem of robust exponential stability for linear parameter-dependent (LPD) neutral systems with mixed time-varying delays and nonlinear perturbations. Based on a new parameter-dependent Lyapunov-Krasovskii functional, Leibniz-Newton formula, decomposition technique of coefficient matrix, free-weighting matrices, Cauchy’s inequality, modified version of Jensen’s inequality, model transformation, and linear matrix inequality technique, new delay-dependent robust exponential stability criteria are established in terms of linear matrix inequalities (LMIs). Numerical examples are given to show the effectiveness and less conservativeness of the proposed methods.

Further improvement on delay-dependent robust stability criteria for neutral-type recurrent neural networks with time-varying delays

Delay-dependent stability of descriptor neutral systems with mixed delays is investigated in this paper. Based on descriptor system approach, some new delay-dependent stability and robust stability criteria are established in terms of a operator and linear matrix inequalities(LMIs). Lyapunov-Krasovskii functional and Leibniz-Newton formula are applied to find the stability results.

Novel delay-dependent asymptotic stability criteria for neural networks with time-varying delays

This paper deals with the problem of robust stability of uncertain neutral type singular system with neutral and discrete delays. By employing a new integral inequality, a delay-dependent robust stability criterion is obtained in the form of linear matrix inequality(LMI). Numerical examples illustrate the effectiveness of this approach and the improvement over previous methods.

Novel delay-dependent robust stability criterion of delayed cellular neural networks

This paper considers the problem of delay-dependent robust stability for uncertain systems with interval time-varying delays. By using the direct Lyapunov method, a new Lyapunov-Krasovskii (L-K) functional is introduced based on decomposition approach, when dealing with the time derivative of L-K functional, a new tight integral inequality is adopted for bounding the cross terms. Then, a new less conservative delay-dependent stability criterion is formulated in terms of linear matrix inequalities (LMIs), which can be easily solved by optimization algorithms. Numerical examples are given to show the effectiveness and the benefits of the proposed method.

In this paper, the problem of stochastic robust stability of interval time-varying delay neural networks with Markovian jump parameters is investigated. The jumping parameters are modeled as a continuous-time, discrete-state Markov process. The linear factional uncertainty is considered, it means that a less conservative result will be obtained than using norm-bounded parameter uncertainties. And the derivative of the delay function can exceed one. Based on the lyapunov-krasovskii functional approach, a new delay-dependent stochastic stability criteria is presented in terms of linear matrix inequalities (LMIs). A numerical example is given to illustrate the effectiveness of the proposed method.

This brief investigates the problem of global exponential stability analysis for discrete recurrent neural networks with time-varying delays. In terms of linear matrix inequality (LMI) approach, a novel delay-dependent stability criterion is established for the considered recurrent neural networks via a new Lyapunov function. The obtained condition has less conservativeness and less number of variables than the existing ones. Numerical example is given to demonstrate the effectiveness of the proposed method.

In this paper, we present an improved delay-dependent absolute stability criterion for Lur’e systems with time delays. The guarantee of absolute stability is provided by Lyapunov-Krasovskii theorem with the Lyapunov functional containing the integral of sector-bounded nonlinearities. The Lyapunov functional terms involving delay are partitioned to be associated with each equidistant fragment on the length of time delay. Employing the Jensen inequality and S-procedure, the sufficient condition is derived from time derivative of the Lyapunov functional. Then, the absolute stability criterion expressed in terms of linear matrix inequalities (LMIs) can be efficiently solved using available LMI solvers. The bisection method is used to determine the maximum allowable time delays to ensure the stability of Lur’e systems in the presence of uncertain time-invariant delays. In addition, the stability criterion is extended to Lur’e systems subject to norm-bounded uncertainties by using the matrix eliminating lemma. Numerical results from two benchmark problems show that the proposed criteria give significant improvement on the maximum allowable time delays.

A delay decomposition approach to robust stability analysis of uncertain systems with time-varying delay

This paper investigates the robust stability for a class of uncertain neutral system with time-varying delay and nonlinear uncertainties. A new delay-dependent stability criteria is presented by using Lyapunov method. The stability criteria for such systems in terms of linear matrix inequalities (LMIS). Some numerical examples show that the effectiveness and the significantly important over some existing results.

This paper is concerned with the problem of robust stability of uncertain linear systems. The considered system has an interval time-varying delay and norm-bounded uncertainty. Based on a new Lyapunov-Krasovskii functional, which considers the fraction of both the lower and upper bounds of the interval time-varying delay, a delay-dependent criteria for robust stability is established in terms of strict linear matrix inequality (LMI). A numerical example illustrates the effectiveness of the approach and the improvement over previous methods.

Discrete bilinear stochastic systems with time-varying delay: Stability analysis and control synthesis