Self-triggered distributed model predictive control for cooperative diving of multi-AUV system. (1st January 2023) - Bian, Yougang; Zhang, Junjie; Hu, Manjiang; Du, Changkun; Cui, Qingjia; Ding, Rongjun
Abstract: This paper investigates the issue of cooperative diving of a multi-autonomous underwater vehicle (AUV) system using self-triggered distributed model predictive control (DMPC). Firstly, a basic DMPC approach is proposed to realize cooperative diving, where a stability condition is derived to facilitate control design. Then, the self-triggering mechanism is introduced into the basic DMPC approach to further save communication and computation resources. The triggering interval is determined with the maximum time instant satisfying the terminal constraint after solving the optimization problem, and this helps reduce the computation burden at each control loop. The feasibility and Lyapunov stability of the self-triggered DMPC approach are analyzed. Numerical simulation is provided to verify the effectiveness of the proposed method. Highlights: A basic DMPC approach is designed to solve the cooperative diving problem of the multi-AUV system. The feasibility and stability of the basic DMPC approach are analyzed to derive a sufficient stability condition. A self-triggering mechanism is introduced into the basic DMPC approach to save communication and computation resources. The feasibility and Lyapunov stability of the self-triggered DMPC approach are analyzed.