Event-Triggered Adaptive Control for a Class of Nonlinear Pure-Feedback Systems

In this paper, an event-triggered control scheme is raised for a class of nonlinear pure-feedback systems. A switching threshold strategy of event-triggering is employed such that the communication burden between controllers and actuators can be effectively decreased. The neural networks are introduced to approximate the unknown nonlinear continuous functions appearing in the deign process. According to the stability analysis, it can be seen that the closed-loop system is semi-globally uniformly bounded. In addition, the errors between the actual signals and the command signals could converge to some compact sets.