Event-triggered adaptive disturbance rejection for marine surface vehicles with unknown dynamics and disturbances. (15th January 2023)

• Record Type: Journal Article
• Authors: Hu, Xin; Gong, Qingtao; Li, Kangqiang
• Is Part Of: Ocean engineering. Volume 268(2023)
• Publication Date: 2023-01-15
• Subjects: Adaptive disturbance rejection -- Event-triggering -- Marine surface vehicle -- Neural network -- Trajectory tracking; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2022.113379
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: This article presents an event-triggered adaptive disturbance rejection scheme for marine surface vehicles with unknown model dynamics and external disturbances. The ocean environmental disturbances are expressed as a series of sinusoidal superpositions with unknown frequencies, amplitudes and phases. By incorporating the adaptive internal model principle, the disturbance rejection is transformed into the adaptive control problem. The adaptive laws and disturbance filter achieve online disturbance estimations. The adaptive neural backstepping is employed to derive the trajectory tracking control law. The event-triggering mechanism is utilized to reduce the wear and tear of thrusters. The event-triggered adaptive disturbance rejection control does not require a priori knowledge of model dynamics and can be treated as a model-free disturbance estimation and rejection scheme. It is theoretically demonstrated that the closed-loop tracking control system is semi-globally stable and the tracking error can be adjusted to be small. Illustrative results on a 1:70 scaled model CyberShip II validate the control scheme. Highlights: Adaptive internal model principle transforms disturbance rejection into adaptive control. Model-free disturbance online estimations does not require a priori vehicle dynamics. Event-triggering protocol is utilized to reduce the wear and tear of vehicle thrusters.