Adaptive NN-Based Event-Triggered Containment Control for Unknown Nonlinear Networked Systems.

Abstract

This article systematically addresses the distributed event-triggered containment control issues for multiagent systems subjected to unknown nonlinearities and external disturbances over a directed communication topology. Novel composite distributed adaptive neural network (NN) event-triggering conditions and event-triggered controller are raised meanwhile. Furthermore, the designed event-triggered controller is updated in an aperiodic way at the moment of event sampling, which saves the computation, resources, and transmission load. On the basis of the NN-based adaptive control techniques and event-triggered control strategies, the uniform ultimate bounded containment control can be achieved. In addition, the Zeno behavior is proven to be excluded. Simulation is presented to testify the effectiveness and advantages of the presented distributed containment control scheme.