摘要
[目的]针对无人水面艇(USV)受高低频混合多源干扰影响,难以精确获取状态信息及保证跟踪精度的问题,提出一种基于卡尔曼滤波联合扩张状态观测器(KFESO)的多艇分布式协同路径跟踪复合抗扰控制方法。[方法]联合Kalman滤波器构造KFESO用于估计无人艇各阶状态量以及集总扰动。设计分布式状态观测器观测虚拟领航艇速度信息,并根据参考速度估计值以及KFESO输出的位置和速度估计值,基于一致性理论与视线引导律设计运动学协同控制器。在此基础上,再利用反步法与动态面控制技术设计动力学抗扰控制器。使用李雅普诺夫稳定性理论证明控制系统下所有误差信号一致最终有界。[结果]仿真结果表明,所设计的控制方法能够准确获取USV各阶状态,且在高低频混合多源干扰下仍具有良好的跟踪精度与抗干扰能力。[结论]该方法能够缓解状态观测器在估计速度与精度之间的矛盾,提高多艇协同路径跟踪精度。
[Objective]Due to mixed-frequency multi-source disturbances,unmanned surface vehicles(USVs)encounter challenges in accurately capturing state information and ensuring path-tracking precision.To address this issue,a composite anti-disturbance control method based on an extended state observer combined with Kalman filter(KFESO)is proposed for distributed cooperative path following of multiple USVs.[Methods]Firstly,an extended state observer combined with Kalman filter is constructed to estimate the state variables and lumped disturbances of USVs.Secondly,a distributed state observer is designed to obtain the speed information of the virtual leader.Based on the consistency theory and the line-of-sight guidance law,a kinematic cooperative controller is designed by combining the output of the KFESO and the estimated reference speed.Furthermore,a kinetic anti-disturbance controller is designed using the backstepping method and the dynamic surface control technique.The Lyapunov stability theory is employed to prove that all error signals in the control system are uniformly ultimately bounded.[Results]Simulation experiments show that the proposed method can accurately obtain the states of USVs.Under mixed-frequency multi-source disturbances,compared with the standard ESO-based control method,it has higher tracking precision and stronger anti-disturbance ability.Regarding path tracking trajectories,the proposed method achieves reduced lateral deviations and more stable trajectories.For position errors,the convergence times are comparable,but the proposed method effectively eliminates oscillations.In terms of path parameter coordination error,the proposed method can stabilize the formation,whereas the comparison method suffers from high-frequency oscillations.In terms of state estimation accuracy,the proposed method significantly improves the estimation accuracy of various state variables,enables the distributed state observer to effectively estimate the speed of the virtual leader,and achieves smaller errors in speed and control force(moment),effectively mitigating the frequent actuator response to noise.[Conclusion]This method can resolve the trade-off between estimation speed and accuracy in ESO,and improve the precision of multi-USV cooperative path following.
作者
陈浩宇
徐海祥
魏骁
王健
陈伟
CHEN Haoyu;XU Haixiang;WEI Xiao;WANG Jian;CHEN Wei(China Ship Development and Design Center,Wuhan 430064,China;School of Naval Architecture,Ocean and Energy Power Engineering,Wuhan University of Technology,Wuhan 430063,China)
出处
《中国舰船研究》
北大核心
2025年第1期191-202,共12页
Chinese Journal of Ship Research
基金
国家自然科学基金资助项目(52201373)
中央高校基本科研业务费专项资金资助项目(WUT:2024IVA018)。
关键词
无人艇
分布式协同路径跟踪
多源干扰
运动控制
操纵性
unmanned vehicles
distributed coordinated path following
multi-source disturbance
motion control
maneuverability
作者简介
陈浩宇,男,1997年生,硕士,工程师;通信作者:徐海祥,男,1975年生,博士,教授。研究方向:海洋智能装备技术。E-mail:qukaiyang@163.com。
