Model Identification and Trajectory Tracking Control for Vector Propulsion Unmanned Surface Vehicles

Electronics

Guofeng Wang¹  Yunsheng Fan¹  Xiaojie Sun¹ 

[1] College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, China;

关键词: unmanned surface vehicle;    vector propulsion;    model identification;    incomplete underactuated system;    virtual control point;    minimum learning parameter;   

DOI  :  10.3390/electronics9010022

来源: DOAJ

【 摘 要 】

To promote the development of military and civilian applications for marine technology, more and more scientific research around the world has begun to develop unmanned surface vehicles (USVs) technology with advanced control capabilities. This paper establishes and identifies the model of vector propulsion USV, which is widely used at present. After analyzing its actuator distribution, we consider that the more realistic vessel model should be an incomplete underactuated system. For this system, a virtual control point method is adopted and an adaptive sliding mode trajectory tracking controller with neural network minimum learning parameter (NNMLP) theory is designed. Finally, in the simulation experiment, the thruster speed and propulsion angle are used as the inputs of the controller, and the linear and circular trajectory tracking tests are carried out considering the delay effect of the actuator, system uncertainty, and external disturbance. The results show that the proposed tracking control framework is reasonable.

【 授权许可】

Unknown