Song Gao , Jin-Liang Wang , Shun-Yan Ren , Bei Peng
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Performance-barrier-based event-triggered leader–follower consensus control for nonlinear multi-agent systems
This paper investigates the leader–follower consensus issue for a class of nonlinear multi-agent systems (MASs) by putting forth a novel performance-barrier-based event-triggered control mechanism. First, a leader–follower consensus control law is proposed with a derived stability condition for the MASs, and a performance-barrier-based event-triggering mechanism is integrated to reduce control updates while guaranteeing the desired convergence of the Lyapunov function. Subsequently, the presence of the minimum inter-event time (MIET) is analytically established, reinforcing the practical feasibility of the proposed approach in real-world scenarios. In addition, a dynamic average consensus algorithm is incorporated to extend the strategy to distributed MASs. Finally, simulation results verify that the developed control protocol effectively achieves the prescribed convergence performance with strong robustness.
期刊介绍:
Neurocomputing publishes articles describing recent fundamental contributions in the field of neurocomputing. Neurocomputing theory, practice and applications are the essential topics being covered.