Complete results for the delay-dependent robust stability and feedback stabilization of linear neutral systems with unknown-but-bounded uncertainties are developed. New linear matrix inequalities-based delay-dependent stability criteria are derived in a systematic way using a new expanded state-space representation and a new Lyapunov-Krasovskii functional. The results are established without re...

This paper extends the scaled-small gain proposal in [1], modifying the Lyapunov-Krasovskii functional to analyze the robust stability of predictorbased state-feedback controllers for discrete-time systems with model uncertainties and unknown time-varying delays in the control input. Results show that the use of predictors improves the achieved robustness margin over static state feedback in so...

This paper investigates the problems of robust exponential stability and stabilization for uncertain linear non-autonomous control systems with discrete and distributed time-varying delays. Based on combination of the Riccati differential equation approach, linear matrix inequality (LMI) techinque and the use of suitable Lyapunov-Krasovskii functional, new sufficient conditions for the robust e...

This paper is devoted to exponential synchronization for complex dynamical networks with delay and impulsive effects. The coupling configuration matrix is assumed to be irreducible. By using impulsive differential inequality and the Kronecker product techniques, some criteria are obtained to guarantee the exponential synchronization for dynamical networks. We also extend the delay fractioning a...

We present adaptive neural control design for a class of perturbed nonlinear MIMO time-varying delay systems in a block-triangular form. Based on a neural controller, it is obtained by constructing a quadratic-type Lyapunov-Krasovskii functional, which efficiently avoids the controller singularity. The proposed control guarantees that all closed-loop signals remain bounded, while the output tra...

In this paper, delay-dependent stability analysis for neutral type neural networks with uncertain paramters and time-varying delay is studied. By constructing new Lyapunov-Krasovskii functional and dividing the delay interval into multiple segments, a novel sufficient condition is established to guarantee the globally asymptotically stability of the considered system. Finally, a numerical examp...

In this paper, the global uniform asymptotic stability is studied for a class of delayed neutral-type neural networks with reactiondiffusion terms. By constructing appropriate Lyapunov-Krasovskii functional and using the linear matrix inequality (LMI) approach, several sufficient conditions are obtained for ensuring the system to be globally uniformly asymptotically stable. A numerical example ...

For cellular neural networks with time-varying delays, the problems of determining the exponential stability and estimating the exponential convergence rate are investigated by employing the Lyapunov–Krasovskii functional and linear matrix inequality (LMI) technique. A novel criterion for the stability, which give information on the delay-dependent property, is derived. Two examples are given t...

The robust exponential stability is investigated for a class of uncertain neutral-type neural networks with discrete and distributed time-varying delays. By introducing a new vector Lyapunov-Krasovskii functional, using Jensen integral inequality, free-weighting matrix method and linear matrix inequality techniques, delay-dependent sufficient conditions are obtained for exponential stability of...

A problem of assessing stability of retarded dynamical networks is solved in this paper. Subsystems are assumed to be integral input-to-state stable (iISS). Time-delays are allowed to reside in both subsystems and interconnection channels, and may be both discrete and distributed. No assumption is made on the interconnection topology. This paper develops a small-gain methodology for constructin...