Event-triggered-based nonlinear model predictive control for trajectory tracking of underactuated ship with multi-obstacle avoidance

• Published in: Ocean engineering 2022-06, Vol.253, p.111278, Article 111278
• Main Authors: Liu, Cheng, Hu, Qizhi, Wang, Xuegang, Yin, Jianchuan
• Format: Article
• Language: English
• Subjects: Event-triggered; Nonlinear model predictive control; Obstacle avoidance; Trajectory tracking
• ISSN: 0029-8018; 1873-5258
• DOI: 10.1016/j.oceaneng.2022.111278

Trajectory tracking and automatic obstacle avoidance are both cutting-edge problems in controlling underactuated ship; however, they have been generally studied separately due to its challenge in multiple control objectives with fewer actuators. Nevertheless, the obstacles are frequently in the way of trajectory tracking at sea; thus, a novel event-triggered-based nonlinear model predictive control (ENMPC) solution is, for the first time, presented for trajectory tracking of underactuated ship with multi-obstacle avoidance herein. Taking advantage of solving multi-objective control problem of nonlinear model predictive control, the trajectory tracking problem of underactuated ship is devised as an optimization problem. Then, the mechanism for automatic obstacle avoidance is established through designing the output constraints elaborately for the resultant optimization problem; considering the input saturation of ship, the problem of trajectory tracking of underactuated ship with multi-obstacle avoidance is naturally transformed into the optimization problem with input and output constraints herein. In order to improve the efficiency of nonlinear model predictive control, an event-triggered control mechanism is designed, i.e., the optimization problem is only solved when the triggering condition is satisfied; to this end, the computational burden is reduced. Finally, comparative simulations are included to validate the effectiveness and advantage of the presented solution. •Event-triggered mechanism reduces optimization times of nonlinear model predictive control.•Trajectory tracking can be formulated as multi-variable optimization control problem.•Collision avoidance can be formulated as output constraints elaborately.