Minimal-Approximation-Based Adaptive Event-Triggered Control of Switched Nonlinear Systems with Unknown Control Direction

In this paper, the adaptive neural network event-triggered tracking problem is investigated for a class of uncertain switched nonlinear systems with unknown control direction and average dwell time switching. To reduce communication traffic, an event-triggering mechanism based on error explored in controller-to-actuator channel. Additionally, minimal approximation technology, which designs virtual laws as unavailable intermediate signals, introduced to difficulty controller design process. Compared existing backstepping using filtering controllers are recursed into lumped function settle explosion complexity, one employed recursive Meanwhile, boundedness lemma Nussbaum given address under framework. The stability overall closed-loop system rigorously proved by Lyapunov theory, rationality proposed strategy verified simulation example. According mechanism, 81.25% resources saved