无人船路径跟随控制方法综述  

An Overview of Path Following Control Methods for Unmanned Surface Vehicles

作　　者：张旋武 谢磊[1,2] 初秀民[1,2,4] 谢朔 柳晨光 张代勇[1,2,3] ZHANG Xuanwu;XIE Lei;CHU Xiumin;XIE Shuo;LIU Chenguang;ZHANG Daiyong(Intelligent Transportation Systems Research Center,Wuhan University of Technology,Wuhan 430063,China;National Engineering Research Center for Water Transport Safety,Wuhan University of Technology,Wuhan 430063,China;School of Energy and Power Engineering,Wuhan University of technology,Wuhan 430063,China;College of Physics and Electronic Information Engineering,Minjiang University,Fuzhou 350108,China)

机构地区：[1]武汉理工大学智能交通系统研究中心,武汉430063 [2]武汉理工大学国家水运安全工程技术研究中心,武汉430063 [3]武汉理工大学能源与动力工程学院,武汉430063 [4]闽江学院物理学与电子信息工程系,福州350108

出　　处：《交通信息与安全》2020年第1期20-26,共7页Journal of Transport Information and Safety

基　　金：国家自然科学基金项目(51709220);国家重点研发计划(2018YFB1600400);工信部高技术船舶研发专项(MC-201920-X01);福州市科技计划项目(2018-G-92)资助。

摘　　要：无人船路径跟随控制同时存在非线性、时延、系统模型不确定以及风、浪、流干扰等问题,使得无人船高精度路径跟随控制的实时性控制难以保证。分析目前几种主要的路径跟随控制方法,PID、反馈线性化以及反步法在无人船航行存在高度非线性时,控制精度难以满足需求;滑模控制的抖振处理方法仍可以进一步优化;模型预测控制的实时性和精确性难以兼顾;模糊逻辑控制为提高控制精度,通常需增大模糊规则库,导致计算复杂;强化学习等智能控制算法在无人船路径跟随控制中具有较大的应用前景,但控制性能有待提高,且缺乏相关试验。基于此,总结了可能提高PID、反馈线性化和反步法控制精度的方法,提出将分层控制思想用于解决复杂模糊规则库和模型预测控制的计算复杂问题,并展望了强化学习等智能控制在无人船路径跟随控制中的可能的发展方向。The problems of non-linearity,time delay,system model uncertainty,and interference of wind,wave,and current are present in path following of unmanned surface vehicle(USV),which make it difficult to precisely control an USV in real-time. Therefore,several major methods of path following are analyzed. PID,feedback linearization,and backstepping are difficult to meet requirements of control precision when the motion of an USV is highly nonlinear. Approaches that can suppress chattering of sliding mode control can be further optimized. For model predictive control,it is difficult to obtain high precision in real time. To improve control precision of fuzzy logic control,it is usually requires an increase in fuzzy rule base,resulting in complicated calculation. Intelligent control algorithms such as reinforcement learning have great application prospects,but the control performance needs to be improved and lack of relevant tests. Based on these,possible methods to improve control precision of PID,feedback linearization,and backstepping are summarized,and hierarchical control theory is introduced to solve the complicated calculation problem of fuzzy control and model predictive control. The possible directions for development of intelligent control such as reinforcement learning in USV path following control are shown.

关 键 词：智能船舶 无人船 路径跟随 控制算法 

分 类 号：U675.91[交通运输工程—船舶及航道工程]