Adaptive Bipartite Output Tracking Consensus in Switching Networks of Heterogeneous Linear Multiagent Systems Based on Edge Events

作者：Juan Zhang, Huaguang Zhang, Yuling Liang, Weizhao Song · 发表于：IEEE Transactions on Neural Networks and Learning Systems · 年份：2021 · DOI：10.1109/tnnls.2021.3089596 · 被引用次数：60 · 研究领域：Distributed Control Multi-Agent Systems、Neural Networks Stability and Synchronization、Stability and Control of Uncertain Systems

This article focuses on the problem of adaptive bipartite output tracking for a class of heterogeneous linear multiagent systems (MASs) by asynchronous edge-event-triggered communications under jointly connected signed topologies. By designing the observers to estimate the states of followers and the dynamic compensators to estimate the states of zero input and nonzero input leader, respectively, the fully distributed edge-event-triggered control protocol is presented. Moreover, it is proven that the bipartite output tracking problem is implemented, and the systems do not exhibit Zeno behavior under a fully distributed control strategy with edge-event-triggered mechanisms. Compared with the existing works, one of the highlights of this article is the design of triggering mechanisms, under which the leader avoids continuous information transmission and any pair of followers that make up the edge asynchronously transmit information through the edge. The methods greatly avoid unnecessary information transmission in the systems. Finally, several simulation examples are introduced to demonstrate the theoretical results obtained in this article.