摘要
环境干扰下如何实现精确、可靠路径跟踪控制是目前无人水面船(无人船)自主航行的关键和难点问题。从无人船路径跟踪控制的算法设计、系统实现和试验验证等三个层面开展研究:在算法设计层面,提出了考虑水流干扰条件下的自适应视距(Line-of-sight,LOS)制导算法以及基于LEM(Line-of-sight&extended state observer&model predictive control,视距-扩张状态观测器-模型预测控制)的自适应路径跟踪控制方法;在系统实现层面,设计了无人船路径跟踪控制系统架构,并解决了MPC快速求解、系统状态采集与不可测状态观测问题;在试验验证层面,构建了在室外水池环境下的模型船路径跟踪控制试验平台,并在此平台上完成了MPC与比例-积分-微分(Proportional-integral-derivative,PID)路径跟踪控制对比试验,以及基于LEM与基于传统LOS的MPC路径跟踪控制(Traditional LOS&MPC,TLM)对比试验。试验结果表明,构建的无人船路径跟踪控制系统运行稳定可靠,提出的LEM自适应路径跟踪控制方法具有更高的路径跟踪控制精度和可靠性。
The accurate and reliable path following control under environmental disturbances is key and difficult for the autonomous navigation of unmanned surface vehicles(USV).An adaptive path following control system with three levels,i.e.,algorithm design,system realization and experimental verification is studied.Specifically,on the algorithm level,an adaptive line-of-sight(LOS)navigation algorithm and an LEM(Line-of-sight&extended state observer&model predictive control)based path following control method is proposed.On the system realization level,an architecture of the proposed adaptive path following control system is designed,and the fast solving problem of MPC and the evaluation problem of unmeasured motion states are solved.On the experimental verification level,a path following control simulation platform based on a model ship is built in the outdoor pool.On the basis of this platform,the comparison experiments on the path following performance between MPC and PID(Proportional-integral-derivative)method,and between LEM and TLM(Traditional LOS&MPC)method are conducted,respectively.The experiment results show that the built platform functions well,and the proposed LEM based path following methods have higher accuracy and reliability than PID based methods.
作者
柳晨光
初秀民
毛庆洲
谢朔
LIU Chenguang;CHU Xiumin;MAO Qingzhou;XIE Shuo(National Engineering Research Center for Water Transport Safety,Wuhan University of Technology,Wuhan 430063;State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan 430079;School of Remote Sensing and Information Engineering,Wuhan University,Wuhan 430079)
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2020年第8期216-227,共12页
Journal of Mechanical Engineering
基金
中国博士后科学基金(2018M632923)
中央高校基本科研业务费专项(203144003)
武汉市科技计划(2017010201010132)资助项目。
关键词
无人水面船
路径跟踪
自适应控制
模型预测控制
视距制导
unmanned surface vehicle
path following
adaptive control
model predictive control
line-of-sight
