NOVEL CONSENSUS ALGORITHM FOR FLEXIBLE MULTI-AGENT SYSTEMS WITH UNCERTAINTIES

Abstract

This paper presents the novel consensus algorithm that drives a group of agents to achieve same behaviors. The algorithm features as flexible and robust design that includes cooperative law and adaptive law. The proposed approach can adapt to different network topology as long as the network has a spanning tree. The cooperative law utilizes local information from available neighbors and drives agents to achieve global consensus. The adaptive law rejects the local disturbances so that the uncertainties do not affect network. Thus, the multi-agent systems arrive locally and globally convergence. The simulation results for different network topology verify proposed flexible consensus algorithm.