Huilan Yang

Extended dissipative exponential synchronization of complex dynamical systems with coupling delay and sampled-data control

Abstract In this paper, by proposing a sampled-data feedback control scheme, we investigate the sampled-data control problem for exponential synchronization of complex dynamical systems with coupling delay. Through constructing a novel Lyapunov functional, which takes a full consideration of the information of t − t k and t k + 1 − t , ∀ t ∈ [ t k , t k + 1 ) , a new sufficient synchronization criterion is obtained based on the Lyapunov stability theory. Further, we consider the extended dissipativity analysis problem, which contains the H ∞ performance, passivity performance, dissipativity performance and L 2 − L ∞ performance in a unified framework, and a sufficient condition in terms of strict LMIs is derived. Finally, simulation examples are employed to demonstrate the effectiveness and the reduced conservatism of the proposed method.

New result on synchronization of complex dynamical networks with time-varying coupling delay and sampled-data control

In this paper, the sampled-data synchronization control problem is investigated for complex dynamical networks (CDNs) with time-varying coupling delay. By constructing a suitable Lyapunov-Krasovskii functional containing some novel triple integral terms with sufficient information about the actual sampling pattern, and together with a general inverse of first-order technique and some effective integral inequalities, less conservative conditions are given in terms of linear matrix inequalities (LMIs) to guarantee the synchronization of sampled-data CDNs with time-varying coupling delay. Numerical examples are provided to illustrate the effectiveness and less conservativeness of the proposed approaches.

Synchronization of nonlinear complex dynamical systems via delayed impulsive distributed control

This paper investigates the exponential synchronization problem of nonlinear complex dynamical systems via delayed impulsive distributed control. Different from the existing results on the synchronization of complex dynamical systems, impulsive input delays are considered in our model. Combined with the time-varying Lyapunov functional and mathematical induction approaches, criteria on system synchronization are established, which sufficiently utilize the information of both the state variables of themselves and their neighbors. Moreover, it is shown that the frequency of impulsive occurrence and impulsive input delays can heavily affect the synchronization performance. Finally, two numerical simulations are given to illustrate the effectiveness of the derived theoretical results.

New and improved results for recurrent neural networks with interval time-varying delay

In this paper, the problem of stability analysis for a class of static recurrent neural networks with interval time-varying delay is considered. By constructing a newly augmented Lyapunov-Krasovskii functional containing triple integral terms and utilizing the inverses of first-order and squared reciprocally convex parameters techniques and zero equality, new and improved delay-dependent stability criteria are proposed to guarantee the asymptotic stability of the concerned networks with the framework of linear matrix inequalities (LMIs). Finally, some numerical examples are given to illustrate the effectiveness of the proposed methods.

Lag synchronization analysis of general complex networks with multiple time-varying delays via pinning control strategy

This paper focuses on the lag synchronization issue for a kind of general complex networks with multiple time-varying delays via the pinning control strategy. By applying the Lyaponov functional theory and mathematical analysis techniques, sufficient verifiable criteria that depend on both intrinsic time-varying delay and coupled time-varying delay are obtained to achieve lag synchronization of the networks. Moreover, the coupling configuration matrices are not required to be symmetric or irreducible, and the minimum number of pinned nodes is determined by node dynamics, coupling matrices, and the designed parameter matrices. Finally, a numerical example is given to illustrate the feasibility of the theoretical results.