Event-triggered adaptive fuzzy fault-tolerant control for autonomous underwater vehicles with prescribed tracking performance

In this paper, we solve the trajectory tracking control problem of autonomous underwater vehicles (AUVs) with actuator faults and model uncertainties. In order to achieve the output tracking with prescribed transient performance, we develop a novel tan-type barrier Lyapunov function (BLF)-based funnel tracking control strategy to constrain the position tracking error of the AUV within prespecified performance funnels. Furthermore, to maintain the predesigned transient tracking performance of the AUV when the actuator fault occurs, an event-triggered adaptive fuzzy fault-tolerant control (FTC) scheme is proposed to compensate actuator faults. Meanwhile, to handle the uncertainties caused by the system model, fuzzy logic systems (FLSs) are adopted to approximate the unknown hydrodynamic parameters and actuator fault parameters. Different from the existing results, the communication burden and the excess wear from the controller to the actuators are reduced utilising the event-triggered mechanism. By using the theory of Lyapunov stability, it is proven that all the signals of the closed-loop system are semiglobally uniformly bounded. Finally, the effectiveness of the proposed method is demonstrated by a simulation example.

Automated summary

This paper addresses the trajectory tracking control problem of autonomous underwater vehicles with actuator faults and model uncertainties. A novel BLF-based funnel tracking control strategy and event-triggered adaptive fuzzy fault-tolerant control scheme are proposed to handle the uncertainties and reduce communication burden and excess wear. The effectiveness of the method is demonstrated through simulation examples.