Event-Based Finite-Time Control for Nonlinear Multiagent Systems With Asymptotic Tracking

In this article, an adaptive neural finite-time event-triggered consensus tracking problem is studied for nonlinear multiagent systems (MASs) under directed graphs. First, the unknown nonlinear functions of MASs can be approximated by neural networks. Then, a distributed adaptive event-triggered control scheme is proposed via command filter and backstepping technique. The newly designed control scheme cannot only circumvent the problem of the explosion of complexity, but also remove the singularity issue typical of conventional backstepping technique. In the meanwhile, an event-triggered mechanism with a dynamic threshold is devised to reduce the waste of network resources. Moreover, by using a novel…

• NN
  National Natural Science Foundation of China

  Awards: 61773188, 62173172, 61973146