Abstract
In this paper, the time-varying formation tracking problem of the general linear multi-agent system is discussed. A distributed formation tracking protocol based on Riccati inequalities with adaptive coupling weights among the follower agents and the leader agent is designed for a leader-following multi-agent system under fixed and switching topologies. The formation configuration involved in this paper is expressed as a bounded piecewise continuously differentiable vector function. The follower agents will achieve the desired formation tracking trajectory of the leader. In traditional static protocols, the coupling weights depend on the communication topology and is a constant. However, in this paper, the coupling weights are updated by the state errors among the neighboring agents. Moreover, the stability analysis of the MAS under switching topology is presented, and proves that the followers also could achieve pre-specified time-varying formation, if the communication graph is jointly connected. Two numerical simulations indicate the capabilities of the algorithms.
Highlights
The research of distributed cooperation and coordination of MAS has received considerable attention in recent years due to the rapid development of computer science and the broad potential application prospects in various fields, such as cooperative surveillance [1], formation control of unmanned aerial vehicles [2], attitude synchronization of spacecrafts [3], swarm intelligence [4] and so on
In order to avoid these limitations, we propose the following distributed consensus protocol with an adaptive time-varying coupling weight c(t), which could be adjusted by the information from the neighbor agents to drive the agent system to achieve the desired time-varying formation
Leader-Following Tracking Control under Switching Topology we will focus on the formation tracking control of the MAS under switching topology, which means the graph Gwill change over time
Summary
The research of distributed cooperation and coordination of MAS has received considerable attention in recent years due to the rapid development of computer science and the broad potential application prospects in various fields, such as cooperative surveillance [1], formation control of unmanned aerial vehicles [2], attitude synchronization of spacecrafts [3], swarm intelligence [4] and so on. In classical static consensus protocol, the designer should acquire the entire communication graph and compute the coupling weights between the neighbor agents. In other words, these consensus protocols cannot be computed and implemented by each agent in a fully distributed way. These consensus protocols cannot be computed and implemented by each agent in a fully distributed way To address this limitation, Li [19] proposed an adaptive control method, which could be updated by the neighbor’s information. Mu proposed a distributed LQR consensus protocol for the quadrotors and two-wheeled mobile robots under a switching directed graph [28].
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