Estimator-based adaptive neural network control of leader-follower high-order nonlinear multiagent systems with actuator faults

摘要

The problem of distributed cooperative control for networked multiagent systems is investigatedrnin this paper. Each agent is modeled as an uncertain nonlinear high-order system incorporatingrnwith model uncertainty, unknown external disturbance, and actuator fault. The communicationrnnetwork between followers can be an undirected or a directed graph, and only some of the followerrnagents can obtain the commands from the leader. To develop the distributed cooperativerncontrol algorithm, a prefilter is designed, which can derive the state-space representation torna newly constructed plant. Then, a set of distributed adaptive neural network controllers arerndesigned by making certain modifications on traditional backstepping techniques with the aid ofrnadaptive control, neural network control, and a second-order sliding mode estimator. Rigorousrnproving procedures are provided,which show that uniform ultimate boundedness of all the trackingrnerrors can be achieved in a networked multiagent system. Finally, a numerical simulation isrncarried out to evaluate the theoretical results.