摘要
[目的]智能船舶在航行过程中由于环境干扰的影响,模型参数的不确定性影响会导致船舶运动控制精度不高,为提高船舶控制算法对干扰的自适应能力,提出一种控制方法。[方法]基于L1自适应控制算法和高斯过程回归(GPR),提出一种欠驱动船舶的航向航迹控制方法,并利用Lyapunov控制函数推导控制律,以证明闭环控制系统一致全局渐近稳定。利用GPR对船舶航行过程中的突发干扰和环境干扰进行建模,并通过与自适应律结合的方式达到快速消除干扰影响的效果。[结果]考虑突发干扰和时变扰动的航向与航迹控制仿真实验结果表明,L1-GPR控制相比传统的L1自适应控制其平均绝对航向误差可减少约9.88%和23.2%,最大绝对航向误差可减少约8.49%和12.1%,能够有效减少环境干扰影响,快速达到稳定状态。[结论]所提航向航迹控制方法能够有效抵抗航行过程中的各种干扰。
[Objectives]Intelligent ships at sea are influenced by environmental interference,and the influence of the uncertainty of model parameters leads to the problem of low ship motion control accuracy,so it is necessary to improve the resistance of the ship's control algorithm to such interference.[Methods]Based on an L1 adaptive control algorithm and Gaussian process regression(GPR)model,an L1 adaptive controller combined with a GPR model controller for underactuated ship path tracking control is proposed,and the control law is derived using the Lyapunov control function.The L1 adaptive controller is a new technique that considers both robustness and fast adaptivity.The closed-loop control system has proven to be consistently globally asymptotically stable,while the GPR model is used to model sudden disturbances and environmental disturbances during ship navigation,and achieve the rapid elimination of the effects of such disturbances in combination with the adaptive law.[Results]The simulation results show that adding the GPR model reduces the average rudder amplitude by 14.9%,average absolute heading error by 23.2%,and maximum absolute heading error by 12.1%.The effects of environmental disturbances can be cancelled out faster and a stable state reached more rapidly than in cases without added disturbances.[Conclusions]The proposed L1-GPR adaptive controller can effectively resist various disturbances during navigation.
作者
李诗杰
何家伟
刘佳仑
刘泰序
徐诚祺
LI Shijie;HE Jiawei;LIU Jialun;LIU Taixu;XU Chengqi(State Key Laboratory of Maritime Technology and Safety,Wuhan 430063,China;School of Transportation and Logistics Engineering,Wuhan University of Technology,Wuhan 430063,China;East Lake Laboratory,Hubei Province,Wuhan,420202,China;National Engineering Research Center for Water Transport Safety,Wuhan 430063,China)
出处
《中国舰船研究》
北大核心
2025年第1期278-288,共11页
Chinese Journal of Ship Research
基金
国家重点研发计划资助项目(2022YFE0125200)
国家自然科学基金资助项目(52272425)
海洋工程全国重点实验室(上海交通大学)开放基金资助项目(GKZD010089)。
关键词
船舶
运动控制
模型参考自适应控制
高斯过程回归
航向控制
航迹控制
ship
motion control
model reference adaptive control
Gaussian process regression(GPR)
heading control
tracking control
