Multistep thrust allocation method based on priority idea for remotely operated underwater vehicle with horizontal thrusters configured as X shape

Author:

Sun Gongwu1ORCID,Xie Jirong1,Qu Junqi1,Li Xinguang1

Affiliation:

1. State Key Laboratory of Deep-Sea Manned Vehicles, China Ship Scientific Research Center, Wuxi, China

Abstract

The horizontal thrusters located as X shape is a commonly used configuration in remotely operated underwater vehicle (ROV). To improve the motion performance of the remotely operated underwater vehicle with this configuration for some typical operation tasks, a multistep thrust allocation method based on priority idea is proposed. Firstly, the thrust allocation result of every single force/moment among the horizontal thrusters is obtained by using a piecewise calculation method. Then, a thrust allocation function of multiple forces and moment is constructed, transforming the thrust allocation problem into a multiparameter optimization problem. The objective function of the optimization problem is established based on priority idea, and limits of the thrusters are considered as constraints. Finally, a thrust redistribution method is adopted in order to further utilize the unsaturated thrusters in the propulsion system. Simulation results show that the proposed thrust allocation method has various advantages over the pseudo-inverse method, which makes the remotely operated underwater vehicle perform perfectly in the given operation task. The proposed method has important practical value and application prospects.

Funder

The Major Scientific and Technological Projects of Hainan Province

Publisher

SAGE Publications

Subject

Artificial Intelligence,Computer Science Applications,Software

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Thruster fault identification using improved peak region energy and multiple model least square support vector data description for autonomous underwater vehicle;Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability;2022-11-30

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