Formation control of multi-agent systems with switching topologies: An ILC-based distributed algorithm design

Abstract

This paper deals with iterative formation control problems for multi-agent systems with switching topologies. Our approach combines consensus protocol algorithms conducted with an iterative learning control update. This leads to networks dynamically changing with evolution along two directions: a finite time axis and an infinite iteration axis. A distributed algorithm is constructed based on nearest neighbor information, and its convergence is established via a Roesser system-based two-dimensional approach. It is shown that a desired relative formation between agents can be achieved along a finite time trajectory if and only if the union of the interaction graphs between the agents over iteration intervals of finite length has a spanning tree for every time step. Simulations are included to illustrate the effectiveness of the derived results.

Consensus Control via Iterative Learning for Singular Multi-Agent Systems With Switching Topologies

“…In actual engineering, due to uncertainties such as disturbances or the limitation of communication range will affect the communication between multi-agents, causing the topology of the multiagent system to change with time, which means that the topology of the system can switch randomly. Therefore, some scholars have studied the coordinated control problem of multi-agent systems with switching topology [31][32][33][34].…”

“…For the singular multi-agent system (33) with the random switching topology shown in Fig. 1 and Fig.…”