Adaptive course-keeping control for unmaned sailboat robot with the speed regulating mechanism

被引：0
|
作者：
Zhang G.-Q. [1 ,2 ]
Li J.-Q. [1 ]
Wang W.-X. [1 ]
Zhang W.-D. [1 ,2 ]
机构：
[1] Navigation College, Dalian Maritime University, Dalian
[2] Department of Automation, Shanghai Jiao Tong University, Shanghai
来源：
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2020年 / 37卷 / 11期
基金：
中国国家自然科学基金;
关键词：
Adaptive control; Gain uncertainty; Radial basic function neural networks; Speed regulating; Unmanned sailboat;
D O I：
10.7641/CTA.2020.90700
中图分类号：
学科分类号：
摘要：
This paper deals with the course-keeping control problem for the unmanned sailboat robot (USR), aiming to the unknown model structure, parameters uncertainty and speed control difficulty in the practical marine environment. For this purpose, a novel robust adaptive course keeping control algorithm with speed regulating is developed. In this algorithm, the radial basic function (RBF) neural network is employed to approximate the structure's uncertainty. Due to the merits of the robust neural damping technique and the dynamic surface control, only two adaptive parameters are designed to compensate the actuators' gain uncertainty. In addition, the information of the neural networks weights parameters is not needed. The USR could converge to the objective course with the desired navigational speed under the proposed controller. Sufficient effort has been made to guarantee that the corresponding error variables satisfies the semi-global uniform ultimate bounded (SGUUB) stability via the Lyapunov theory. Through the computer simulation under the presence of marine environment, the proposed approach could obtain the better performance in aspects of the speed regulating and robustness. © 2020, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.
引用
收藏
页码：2383 / 2390
页数：7
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