Dynamic event-triggered path-following control for underactuated unmanned surface vehicle with obstacle avoidance

This paper introduces an innovative guidance and control algorithm employing a dynamic event-triggered mechanism (DETM) to achieve path-following with obstacle avoidance for the underactuated unmanned surface vehicle (USV) under external disturbances. The algorithm is composed of two main parts: guidance and control. In the guidance part, the desired heading angle is determined by using the line of sight (LOS) and the artificial potential field method (APFM), enabling path-following and obstacle avoidance, respectively. In the control part, the nonlinear gain recursive sliding mode control (NGRSMC) is incorporated into the controller, effectively resolving the conflict between the control precision and dynamic performance while enhancing the robustness of the control system against parameter perturbations. Additionally, the nonlinear disturbance observer estimates unknown external disturbances and compensates for them in the controller, improving control accuracy. Furthermore, dynamically adjustable gain variable and bounded one are designed within the triggering conditions to determine the triggering thresholds, achieving more efficient utilization of communication resources. Besides, the APFM used for obstacle avoidance improves safety during navigation. Finally, it is demonstrated that all variables within the feedback system remain uniformly ultimately bounded (UUB) and simulation results are presented to highlight the superiority and performance of the proposed algorithm.