Event-triggered fixed-time tracking control for uncertain networked autonomous surface vehicle with disturbances

This paper delves into the trajectory tracking problem of networked autonomous surface vehicles (NASV) facing model uncertainty and disturbances. A novel event-triggered strategy, featuring a time-varying threshold and alternative parameters, is devised to optimize the utilization of network resources between the plant and the controller. To succinctly describe the tracking error, the autonomous vehicle system is simplified to a second-order dynamic model. A new event-triggered fixed-time sliding mode control (EFSMC) strategy is formulated to stabilize the sliding system at the origin within a fixed time. This strategy not only diminishes high-frequency chattering but also fulfills convergence performance. The fixed-time stability of the vehicle is validated using the Lyapunov theory. Finally, numerical simulations are conducted to showcase the superiority of the constructed EFSMC in this paper. The simulations illustrate that the control unit reduces the frequency of control protocol transmissions while ensuring stable performance.