摘要
为提高无人水面艇(unmanned surface vehicle,USV)对复杂海况的适应性,针对欠驱动USV的路径跟踪控制问题,设计基于改进的自适应积分视线(improved adaptive integral line-of-sight,IAILOS)制导方法和径向基神经网络(radial basis function neural network,RBFNN)的积分滑模路径跟踪控制器。在IAILOS制导方法中,引入降阶的扩张状态观测器估计未知时变洋流速度,从而使得该制导方法不仅可以估计时变漂角,而且可以补偿未知时变洋流的扰动。利用RBFNN的无限逼近特性来估计USV动力学模型中的不确定项和未知的外部环境干扰。通过稳定性分析和仿真对比实验,验证了本文所设计的控制器的准确性和鲁棒性。
To improve the adaptability of unmanned surface vehicles(USVs)to complex sea conditions,aiming at the path following control of underactuated USVs,an integral sliding-mode path following controller is designed based on the improved adaptive integral line-of-sight(IAILOS)guidance law and the radial basis neural network(RBFNN).The reduced-order extended state observer is introduced to estimate the unknown time-varying ocean current velocity in the IAILOS guidance law,so that the guidance law can not only estimate the time-varying drift angle,but also compensate the disturbances of unknown time-varying ocean currents.The infinite approximation property of RBFNN is used to estimate the uncertain terms in the USV dynamic model and the unknown external environment disturbances.The accuracy and robustness of the controller are verified through the stability analysis and simulation comparison experiments.
作者
白一鸣
刘磊
韩新洁
BAI Yiming;LIU Lei;HAN Xinjie(Marine Electrical Engineering College,Dalian Maritime University,Dalian 116026,Liaoning,China)
出处
《上海海事大学学报》
北大核心
2021年第4期12-19,52,共9页
Journal of Shanghai Maritime University
基金
大连市软科学研究计划(2019J11CY014)。
作者简介
白一鸣(1983-),男,辽宁海城人,高级实验师,博士,研究方向为船舶操纵运动控制,(E-mail)hs_bym@126.com;刘磊(1996-),男,天津人,硕士研究生,研究方向为无人船运动控制,(E-mail)1252073446@qq.com;韩新洁(1969-),女,辽宁大连人,副教授,硕士,研究方向为智能控制,(E-mail)xinjie@dlmu.edu.cn。
