A novel event-triggered robust neural formation control for USVs with the optimized leader–follower structure. (1st September 2021)

• Record Type: Journal Article
• Authors: Zhang, Guoqing; Yu, Wei; Li, Jiqiang; Zhang, Xianku
• Is Part Of: Ocean engineering. Volume 235(2021)
• Publication Date: 2021-09-01
• Subjects: Underactuated vehicles -- Formation control -- Optimized leader–follower structure -- Neural damping technique -- Event-triggered inputs; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2021.109390
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: In this note, one focuses on the application of the event-triggered mechanism into the formation control system of the underactuated surface vehicles (USVs). To avoid the possible singularity problem, a novel fleet control model of the leader–follower structure is established in the Cartesian coordinate frame. The innovation of this design is that the information status between the leader and the follower could be acquired continuously and intuitively. Furthermore, a practical event-triggered robust neural control is developed by utilizing the robust neural damping technique and the input event-triggered rule. When the event-triggered threshold is satisfied, the state variables and the control input could be reset or updated aperiodically. That can effectively reduce the occupancy of the communication network from the controller to the actuator and facilitate its application in the practical engineering. In this algorithm, only four adaptive updated parameters are required in the adaptive model. Such design could compensate the gain uncertainties and the environmental disturbances. Based on the Lyapunov theory, considerable efforts have been made to illustrate that all signals in the closed-loop system are the semi-global uniformly ultimately bounded(SGUUB). Finally, numerical simulations are conducted to demonstrate the validity of the proposed scheme. Highlights: The event-triggered robust neural algorithm is proposed for the formation control of underactuated surface vehicles. The leader–follower structure is optimized to settle the issue of the fleet state's continuous acquisition. The energy consumption and transmission burden can be largely reduced between the controller and actuator. The form of the control law becomes concise by employing robust neural damping techniques.