Event-triggered neural network control of autonomous surface vehicles over wireless network

Abstract

In this paper, an event-triggered neural network control method is proposed for autonomous surface vehicles subject to uncertainties and input constraints over wireless network.An event-triggered mechanism with three logic rules is employed to determine the wireless data transmission of states and control inputs.An event-driven neural network is applied to approximate the uncertainties using aperiodic sampled states.In addition, a predictor is employed to update the weights of neural network.An event-based bounded kinetic control law is applied to address the actuator constraints.The advantage of the proposed event-triggered neural network control approach is that the network traffic can be reduced while guaranteeing system stability and speed following performance.The closed-loop control system is proved to be input-to-state stable via cascade theory.The Zeno behavior can be avoided via the proposed event-triggered neural network control approach.A simulation example is provided to demonstrate the effectiveness of the proposed event-triggered neural network control approach for autonomous surface vehicles.