Proportional-Integral Control for Markovian Jumping Systems with Distributed Time 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.

New results on delay-dependent robust stability criteria of uncertain fuzzy systems with state and input delays

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.

Markovian jumping systems have arisen naturally in the mathematical modeling of phenomena spanning disciplines in the social sciences, natural sciences, and engineering. This kind of stochastic dynamical systems can be employed to model the dynamics when parameters are subject to random abrupt changes due to sudden environment changes, subsystem switching, system noises, executor faults, and so forth. Much attention has been given to modeling, optimization, and real applications of such stochastic dynamical systems in the literature in recent years. As the advanced control and optimization will provide a basis for the design and application of such stochastic systems, these advanced techniques would result in substantial and sustainable benefits. The accepted papers in this special issue include stochastic stability, stabilization, stochastic control optimization, system modeling and identification methods, predictive control, signal processing, robust filtering, multiagent systems, networked control systems, time-delayed systems, neural networks, the Takagi-Sugeno fuzzy systems, simulated annealing, and fault detection methods.

Robust stability criteria for uncertain neutral system with time delay and nonlinear uncertainties

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

The problem of mean square bounded-input bounded-output(BIBO) stability is investigated for a class of discrete-time stochastic control systems with time delays and non-linear perturbations. In this paper, a special point δ in the time delay's variation interval is introduced, and the variation interval is divided into two subintervals. Then, by defining a special Lyapunov-Krasovskii functional and checking its variation in the two subintervals, respectively, some novel delay-dependent stability criteria for the discrete-time stochastic control systems are derived. These conditions are expressed in the forms of linear matrix inequalities(LMIs), whose feasibility can be easily checked by using Matlab LMI Toolbox. Meanwhile, this paper provides a new method for studying discrete-time stochastic mean square BIBO stability. Finally, a numerical example is given to illustrate the validity of the main results.

This paper is concerned with stability criteria of networked control systems (NCSs) with both the time-varying network-induced delay and data packet dropout taken into account. A continuous time model of NCSs with time-varying and uncertainties is proposed. Based on the dividing of the time-varying delay, a new Lyapunov functional is constructed, and a delay-dependent stability criterion is derived to guarantee the globally asymptotic stability of the networked control systems (NCSs). Expressed in terms of linear matrix inequalities (LMIs), the stability condition can be checked using the numerically efficient Matlab LMI Control Toolbox. Compared with some report methods, no slack matrix variable is introduced and the proposed methods gave a much less conservative maximum allowable delay bound (MADB). A numerical example is provided to demonstrate the effectiveness of the proposed method.

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.

On robust stability criterion for dynamic systems with time-varying delays and nonlinear perturbations

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

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.

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.

Based on the Lyapunov-Krasovskii method, the exponential stability in the mean square sense is investigated for Ito stochastic system with time-varying delay. The statistic properties of Ito diffusions, some relaxation matrices, and the convex combination condition on time-varying delay are employed for computing the constructed Lyapunov-Krasovskii functional of a rather general form. A delay-dependent stability criterion is established in terms of linear matrix inequality (LMI). An illustrative example is given to demonstrate the method.