Distributed Consensus of Multi‐Agent Networks Via Event‐Triggered Pinning Control

Abstract

This paper is concerned with distributed consensus between two multi‐agent networks with the same topology structure. Considering one network as the leaders' network and the other one as the followers' network, a new event‐triggered pinning control scheme is proposed to realize distributed consensus between these two networks. By utilizing the graph theory and Lyapunov functional method, consensus criteria are derived in the form of linear matrix inequalities. Moreover, distributed consensus of multi‐agent networks with Lipschitz nonlinear dynamics is also discussed. Numerical simulations are provided to demonstrate the effectiveness of the theoretical analysis.

Tracking Control for Stochastic Multi‐Agent Systems Based on Hybrid Event‐Triggered Mechanism

“…To address the problem mentioned above, event-triggered control approaches have been proposed in [10][11][12][13][14][15][16]. In [10], a continuous event-triggered mechanism based on relative error was proposed for first-order multi-agent systems.…”

“…However, in some cases, this analysis is difficult, especially for stochastic systems. Recently, [14][15][16] proposed a periodic event-triggered mechanism (PETM), in which the event is detected in a discrete way and the inter-event times can be guaranteed at least h. As it is pointed out in [17], when the sampling period is large enough the periodic event-triggered doesn't present any significant improvement compared to the periodic sampling, which requires us to find a new event-triggered mechanism-hybrid event-triggered mechanism (HTEM). The rudiments of HETM are proposed in [18], which is used to study practical stability of single perturbed linear systems.…”

Average Consensus for Multi‐Agent System with Measurement Noise and Binary‐Valued Communication

“…One of the essential aspects in MAS is the consensus problem, which is widespread in many practical situations. For example, the behavior of flocks and swarms [17,21], distributed algorithms [6,19], random networks [2,25], sensor networks [12,14], biological systems [5,24], and so on.…”

Bifurcation control of small‐world networks with delays VIA PID controller

“…Some existing bifurcation dynamics of a given nonlinear model are improved by designing a controller, thereby obtaining some approving dynamical behaviors. Various control processes have been presented on complex networks [12][13][14][15][16][17][18][19][20][21][22], but bifurcation control is rarely cited on the complex network.…”