Decentralized event-triggered cooperative path-following control for multiple autonomous surface vessels under actuator failures

Abstract

This paper investigates the problem of cooperative path-following control for underactuated autonomous surface vessels in the presence of the model uncertainties, environmental disturbance, actuator failures and limited communication. A novel intelligent controller is designed for autonomous surface vessels to track priori parameterized reference paths so that the desired formation can be achieved. In the algorithm, the model uncertainties are estimated by neural networks. By virtue of the dynamic surface control technique, the inherent problem ”explosion of complexity” occurred in the traditional Backstepping design framework is avoided. A concise adaptive law is developed to compensate the upper bound of the weight matrix for neural networks, rather than the whole weight matrix. Furthermore, the event-triggered mechanism is embedded into the cooperative controller to reduce the frequency of inter-vehicle communication. The cooperative controller is updated only at the instant when the threshold condition is violated. By using the Lyapunov theory, both the semi-globally uniformly ultimately bounded and fault-tolerance capability of the closed-loop system are guaranteed. Finally, numerical examples are performed to demonstrate the effectiveness and superiority of the proposed algorithm.