Chien-Yu Lu

An LMI-based approach for robust stabilization of uncertain stochastic systems with time-varying delays

Based on the linear matrix inequality method, we introduce the robust stability of uncertain linear stochastic differential delay systems with delay dependence. The parameter uncertainty is norm-bounded and the delays are time varying. We then extend the proposed theory to discuss the robust stabilization of uncertain stochastic differential delay systems.

Stability of cellular neural networks with time-varying delay

The stability for cellular neural networks (CNNs) with time-varying delay is introduced by using a linear-matrix inequality. A sufficient condition related to the global asymptotic stability for delay CNNs is proposed. It is shown that the condition relies on the dependence of the delay. This condition is less restrictive than that given in the literature.

A Delay-Dependent Approach to Passivity Analysis for Uncertain Neural Networks with Time-varying Delay

This paper deals with the problem of passivity analysis for neural networks with time-varying delay, which is subject to norm-bounded time-varying parameter uncertainties. The activation functions are supposed to be bounded and globally Lipschitz continuous. Delay-dependent passivity condition is proposed by using the free-weighting matrix approach. These passivity conditions are obtained in terms of linear matrix inequalities, which can be investigated easily by using standard algorithms. Two illustrative examples are provided to demonstrate the effectiveness of the proposed criteria.

On improved delay-dependent robust stability criteria for uncertain systems with multiple-state delays

This brief provides new stability criteria for a class of uncertain linear time-delay systems with time-invariant delays. Based on Lyapunov-Krasovskii functionals combining with LMI techniques, simple and improved delay-dependent robust stability criteria. which are given in terms of quadratic forms of state and LMI, are derived. Our results shown by two examples are less conservative than the existing stability criteria.

On robust stabilization of uncertain stochastic time-delay systems—an LMI-based approach

In this paper, we first deal with the robust stability of uncertain linear stochastic differential delay systems. The parameter uncertainties are time-varying and unknown but are norm-bounded via two types of uncertainties, and the delays are time invariant. We then extend the proposed theory to discuss the robust stabilization of uncertain stochastic differential delay systems. These results are given in terms of linear matrix inequalities. Two examples are presented to illustrate the effectiveness.

Robust H/sub /spl infin// control for uncertain nonlinear stochastic neutral systems with state delays

This paper deals with the problem of robust stability and robust H/sub /spl infin// control for a class of uncertain neutral systems. The nonlinearities are assumed to satisfy the global Lipschitz conditions and appear in the term of perturbation. Attention first is focused on investigating a sufficient condition for designing a state feedback controller which stabilizes the uncertain neutral system under consideration of robust stabilization dependent of delay. Then, we show that it guarantees an H/sub /spl infin//-norm bound constraint on the disturbance attenuation. The proposed results are given in terms of linear matrix inequalities. An example is worked out to illustrate the validness of the theoretical results.

Delay-Range-Dependent Global Robust Passivity Analysis of Discrete-Time Uncertain Recurrent Neural Networks with Interval Time-Varying Delay

This paper examines a passivity analysis for a class of discrete-time recurrent neural networks (DRNNs) with norm-bounded time-varying parameter uncertainties and interval time-varying delay. The activation functions are assumed to be globally Lipschitz continuous. Based on an appropriate type of Lyapunov functional, sufficient passivity conditions for the DRNNs are derived in terms of a family of linear matrix inequalities (LMIs). Two numerical examples are given to illustrate the effectiveness and applicability.

Delay-dependent robust H ∞ filtering for interval systems with state delays

This paper deals with the problem of robust H∞ filtering for a class of linear continuous-time interval systems with delay dependence and structured uncertainties, which are not restricted to the matched uncertainty or the norm-bounded uncertainty. The problem aims at designing a stable linear filtering assuring asymptotic stability and a prescribed H∞ performance level for the filtering error system. A sufficient condition for the existence of such a filter is developed in terms of linear matrix inequalities. A numerical example demonstrates the validity of the newly developed theoretical results.

Robust Kalman filtering for delay-dependent interval systems

In this paper, we study the problem of Kalman filtering for a class of linear continuous-time interval systems with delay-dependent conditions. By employing a Lyapunov-Krasovskii functional approach, it is proven that the dynamics of the estimation error is stochastically exponential stable in the mean square. Sufficient conditions are proposed to guarantee the existence of the desired robust Kalman filters by solving linear matrix inequality which is delay dependent. A numerical example is worked out to illustrate the validity of the theoretical results.

Robust stabilization of uncertain discrete time systems with state delay

In this paper, we first deal with the robust stability of uncertain linear discrete time systems. The parameter uncertainties are unknown but are norm-bounded, and the system involves state time delay. Moreover, we extend the introduced theory to discuss the robust stabilization of uncertain linear discrete time systems. The presented results are given in terms of linear matrix inequalities. An example demonstrates the effectiveness of the proposed approach.