Exponential synchronization of discrete-time impulsive dynamical networks with time-varying delays and stochastic disturbances

Event-Triggered Exponential Synchronization of the Switched Neural Networks With Frequent Asynchronism

The synchronization for a class of switched uncertain neural networks (NNs) with frequent asynchronism based on event-triggered control is researched in this article. Compared with existing works that require one switching during an inter-event interval, frequent switching is allowed in this article. By employing controller-mode-dependent Lyapunov-Krasovskii functionals (LKFs), we devise the control strategy to guarantee that the switched NNs can be synchronized. The proposed LKFs can make full use of system information. Using an improved integral inequality, some sufficient stability conditions formed by linear matrix inequalities (LMIs) are derived for the synchronization of switched uncertain NNs. Average dwell time (ADT) is obtained in the form of inequality that includes the maximum inter-event interval. In addition, the existence of lower bound of inter-event interval is discussed to avoid Zeno behavior. At last, the feasibility of the proposed method is proven by a numerical example.

Finite-Time Pinning Synchronization Control for T-S Fuzzy Discrete Complex Networks with Time-Varying Delays via Adaptive Event-Triggered Approach

This paper is concerned with the adaptive event-triggered finite-time pinning synchronization control problem for T-S fuzzy discrete complex networks (TSFDCNs) with time-varying delays. In order to accurately describe discrete dynamical behaviors, we build a general model of discrete complex networks via T-S fuzzy rules, which extends a continuous-time model in existing results. Based on an adaptive threshold and measurement errors, a discrete adaptive event-triggered approach (AETA) is introduced to govern signal transmission. With the hope of improving the resource utilization and reducing the update frequency, an event-based fuzzy pinning feedback control strategy is designed to control a small fraction of network nodes. Furthermore, by new Lyapunov–Krasovskii functionals and the finite-time analysis method, sufficient criteria are provided to guarantee the finite-time bounded stability of the closed-loop error system. Under an optimization condition and linear matrix inequality (LMI) constraints, the desired controller parameters with respect to minimum finite time are derived. Finally, several numerical examples are conducted to show the effectiveness of obtained theoretical results. For the same system, the average triggering rate of AETA is significantly lower than existing event-triggered mechanisms and the convergence rate of synchronization errors is also superior to other control strategies.

Non-fragile synchronization of complex dynamical networks with hybrid delays and stochastic disturbance via sampled-data control

This paper focuses on the global synchronization issue for a class of the complex dynamical networks (CDNs) with hybrid delays and stochastic disturbance. The hybrid delays consider two forms: discrete-time coupling delays and distributed coupling delays. The non-fragile sampled-data control protocol, which is allowed to norm-bounded uncertainty, is considered for the first time in this paper. Next, by applying a new augmented Lyapunov-Krasovskii functional (LKF), with the aid of the convex combination method and the stochastic analysis technique, a less conservative condition is derived to ensure that the considered CDNs can achieve the global synchronization with hybrid delays and stochastic disturbance under a non-fragile sampled-data control strategy. Finally, there exists three simulation examples to verify the effectiveness and advantages of the analytical results.