文献类型：期刊文献

英文题名：Adaptive neural network control of a marine surface vessel with output constrains

作者：Chen, Guangjun[1,2]; Tian, Xuehong[1,2]; Liu, Haitao[1,2]

机构：[1] School of Mechanical and Power Engineering, Guangdong Ocean University, Zhanjiang, 524088, China; [2] Southern Marine Science and Engineering Guangdong Laboratory [Zhanjiang], Zhanjiang, 524000, China

年份：2020

起止页码：883

外文期刊名：Proceedings - 2020 35th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2020

收录：EI(收录号：20210809967074)

语种：英文

外文关键词：Adaptive control systems - Lyapunov functions - Numerical methods - Uncertainty analysis

外文摘要：In this article, an adaptive neural network (NN) trajectory tracking control is proposed for a marine surface vessel with output constraints and uncertainties. The second-order linear tracking differentiator was employed to cope with differential blast problem, an adaptive NN is adopted to estimate the uncertainty models and unknown disturbances, and an asymmetric barrier Lyapunov function (BLF) is used to handle the output constrains problems. Moreover, it is proven that the multiple output limits are never violated, the asymptotic tracking can be implemented, and all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB). A numerical simulation are demonstrated the availability of the proposed methods. ? 2020 IEEE.