PI-Type Iterative Learning Consensus Control for Second-Order Hyperbolic Distributed Parameter Models Multi-Agent Systems

Abstract

This paper considers the consensus control problem of multi-agent systems (MAS) with second-order hyperbolic distributed parameter models. Based on the framework of network topologies, a PI-type iterative learning control protocol is proposed by using the nearest neighbor knowledge. Using Gronwall inequality, a sufficient condition for the convergence of the consensus errors with respect to the iteration index is obtained. Finally, the validity of the proposed method is verified by two numerical examples.

Keywords

• Multi-agent systems
• iterative learning control
• Gronwall inequality
• hyperbolic distributed parameter system