Distributed Leader-Follower Consensus for Uncertain Multi-Agent Systems With Time-Triggered Switching of the Communication Network

Abstract A distributed adaptive control strategy is developed for heterogeneous multi-agent systems in nonlinear Brunovsky form with p-dimensional nth-order dynamics, operating under time-triggered switching communication topologies. The approach integrates bounded proximity-dependent repulsive potential functions for agent-agent, agent-leader, and agent-obstacle proximity management with neural-network estimators for compensating system uncertainties and disturbances. The resulting distributed control and adaptive laws, together with dwell-time requirements for topology transitions, achieve leader-following consensus. This integrated design provides synchronized formation and robust disturbance rejection in evolving network configurations, and its effectiveness is demonstrated through multiple numerical simulations.