Synchronization Control for A Class of Discrete Time-Delay Complex Dynamical Networks: A Dynamic Event-Triggered Approach

Abstract

This paper is concerned with the synchronization control problem for a class of discrete time-delay complex dynamical networks under a dynamic event-triggered mechanism. For the efficiency of energy utilization, we make the first attempt to introduce a dynamic event-triggering strategy into the design of synchronization controllers for complex dynamical networks. A new discrete-time version of the dynamic event-triggering mechanism is proposed in terms of the absolute errors between control input updates. By constructing an appropriate Lyapunov functional, the dynamics of each network node combined with the introduced event-triggering mechanism are first analyzed, and a sufficient condition is then provided under which the synchronization error dynamics is exponentially ultimately bounded. Subsequently, a set of the desired synchronization controllers is designed by solving a matrix inequality. Finally, a simulation example is provided to verify the effectiveness of the proposed dynamic event-triggered synchronization control scheme.

Nonfragile H∞ filtering for discrete multirate time‐delayed systems over sensor networks characterized by Gilbert‐Elliott models

“…Future research topics will include the investigation on the filtering problems for systems over sensor networks with event‐triggered protocol, dynamic event‐triggered protocol, Round‐Robin protocol, and signal quantizations . Also, the multiobjective optimization problem can be considered to deal with the tradeoff issue on the impacts from multirate sampling, time‐delays, packet dropouts, and filter gain variations.…”

Consensus of a multi-agent systems with heterogeneous delays

“…One can also mention application of event-triggering mechanism for synchronization of multi-agent systems, e. g. in [13], where also sensor saturation is taken into account. A similar problem for discrete-time systems, namely event-triggered synchronization of complex networks, is studied in [12].…”

Mobile robot localization under stochastic communication protocol

“…However, the transmission of the measurement data will increase the burden of communication network as the number of sensors increases. In order to ease the network burden or avoid the network congestion, the communication protocols have been often adopted in the networked systems such as weighted try-oncediscard protocol [39], round-robin protocol [6,26], event-triggered protocol [11,15,20,29], stochastic communication protocol (SCP) [9,38], and so on.…”