Adaptive neural path-following control for underactuated ships in fields of marine practice
Adaptive neural path-following control for underactuated ships in fields of marine practice
复制标题
海洋实践领域欠驱动船舶的自适应神经路径跟踪控制
DOI：
10.1016/j.oceaneng.2015.05.013
复制
发表时间：
2015-08
影响因子：
5
通讯作者：
Zheng Yunfeng
中科院分区：
文献类型：
--
作者：
Zhang Guoqing;Zhang Xianku;Zheng Yunfeng
本文研究了基于航路点的不确定欠驱动船舶鲁棒自适应路径跟踪控制问题。提出了一种基于“逻辑虚拟船”的航向控制律，用于规划合理的参考航线，为实际工程中的欠驱动船舶提供指导。在此基础上，利用动态面控制技术、神经网络逼近和极坐标方法，提出了一种实用的自适应神经控制算法。利用李雅普诺夫综合方法，得到了闭环控制系统的半全局一致最终有界稳定性。所提出的控制方案的优点在于：第一，它可以解决“基于航路点的导航”的实际问题，这对现有的理论算法在控制工程中的应用具有重要意义;第二，所提出的神经网络控制器能够在不需要水动力阻尼结构和海洋扰动的情况下捕获航行器的不确定性。这些特点将有助于该算法在海上实践中的实施。两个数值例子说明了所提出的方法的性能和有效性。
In this note, one concerns with the problem of robust adaptive path-following control for uncertain underactuated ships in fields of marine practice: waypoints based navigation. A novel “logical virtual ship (LVS)” based steering law is developed to programme the rational reference route, which is to guidance the underactuated ship in the practical engineering. Furthermore, a practical adaptive neural control algorithm is proposed by virtue of the dynamic surface control (DSC) technique, neural networks approximation and polar coordinates scheme. And much effort are made to obtain semi-global uniform ultimate bounded stability for the closed-loop control system, using the Lyapunov synthesis. The advantages of the developed control scheme are that first, it could tackle the practical condition “waypoints based navigation”, which is very meaningful for applying the existed theoretical algorithm in control engineering; second, the developed neural controller is able to capture the vehicle uncertainties without the exact information of hydrodynamic damping structure and the sea disturbances. These characteristics would facilitate the implementation of the algorithm in the marine practice. Two numerical examples have been given to illustrate the performance and effectiveness of the proposed scheme.
登录
查看更多内容
DOI：
10.3182/20080706-5-kr-1001.02706
发表时间：
2008
期刊：
IFAC Proceedings Volumes
影响因子：
--
作者：
M. Breivik;Vegard Hovstein;T. Fossen
通讯作者：
M. Breivik;Vegard Hovstein;T. Fossen
DOI：
10.1002/9781119575016
发表时间：
2011-05
期刊：
--
影响因子：
--
作者：
T. Fossen
通讯作者：
T. Fossen
影响因子：
6
作者：
Yansheng Yang;Xiao-Feng Wang
通讯作者：
Yansheng Yang;Xiao-Feng Wang
影响因子：
4.8
作者：
K. P. Tee;S. Ge
通讯作者：
K. P. Tee;S. Ge
影响因子：
11.9
作者：
Weisheng Chen;L. Jiao;Rui-hong Li;Jing Li
通讯作者：
Weisheng Chen;L. Jiao;Rui-hong Li;Jing Li