电光与控制, 2022, 29 (11): 17, 网络出版: 2023-02-10  

基于有限时间和状态观测器的双闭环AUV轨迹跟踪控制研究

Dual Closed-Loop AUV Trajectory Tracking Control Based on Finite Time and State Observer
作者单位
1 徐州徐工汽车制造有限公司, 江苏 徐州 221000
2 江苏科技大学电子信息学院, 江苏 镇江 212000
摘要
为解决欠驱动AUV轨迹跟踪中系统收敛速度慢、易发散、模型不确定等问题, 提出了一种有限时间和降阶状态观测器双环闭合的运动控制策略。根据时间尺度原理分为位置控制环和姿态控制环, 位置控制环使用有限时间控制方法来加快位置量的收敛速度; 姿态控制环采用基于降阶扩张状态观测器的动态积分滑模来实现对姿态角的快速收敛和补偿混合不确定项。在三维仿真环境下模拟AUV轨迹跟踪的控制效果, 通过仿真结果可看出: 所设计的控制器在收敛速度、控制精度、鲁棒性及跟踪效果方面均高于常见的轨迹跟踪器, 能较好地满足欠驱动AUV的轨迹跟踪控制需要。
Abstract
In order to solve the problems of slow convergence speed,easy divergence and uncertain model in under-driven AUV trajectory tracking,a dual closed-loop control strategy based on finite-time and reduced-order state observer is proposed.According to the principle of time scale,it is divided into position control loop and attitude control loop.The position control loop adopts finite time control method to speed up the convergence of position quantity.The attitude control loop adopts dynamic integral sliding mode based on the reduced-order extended state observer to quickly converge the attitude angle and compensate for the mixed uncertainties.The control effect of AUV trajectory tracking is simulated in 3D simulation environment.The simulation results show that the convergence speed,control accuracy,robustness and tracking effect of the proposed controller are higher than those of conventional trajectory trackers,and it can better meet the trajectory tracking control needs of under-driven AUV.
参考文献

[1] YAN Z P,WANG M,XU J.Global adaptive neural network control of underactuated autonomous underwater vehicles with parametric modeling uncertainty[J].Asian Journal of Control,2019,21(3):8-16.

[2] YAN Z P,GONG P,ZHANG W,et al.Model predictive control of autonomous underwater vehicles for trajectory tracking with external disturbances [J].Ocean Engineering,2020(87):147-154.

[3] LI D,DU L.AUV trajectory tracking models and control strategies:a review[J].Journal of Marine Science and Engineering,2021,9(9):89-94.

[4] LEI M,LI Y,PANG S.Extended state observer-based composite-system control for trajectory tracking of underactuated AUVs[J].Applied Ocean Research,2021,112(7):65-73.

[5] 许文瑶,贺继林.基于改进速度障碍法的水下机器人动态避障 [J].电光与控制,2021,28(12):86-90.

[6] 丁力,虞青,刘凯磊,等.系留式无人机抗干扰轨迹跟踪控制研究[J].电光与控制,2020,27(12):95-100.

[7] 陈奕梅,康雪晶,徐鹏.复杂环境下多移动机器人控制算法研究[J].电光与控制,2021,28(4):48-52.

[8] 姚绪梁,王晓伟,蒋晓刚,等.海流干扰下的欠驱动AUV三维路径跟踪控制[J].哈尔滨工业大学学报, 2019,51(3):37-45.

[9] 蒲明,刘鹏,熊皑,等.固定时间收敛动态面Backstepping控制[J].电光与控制,2020,27(10):66-72,77.

[10] 韩亚楠.复杂海洋环境下的欠驱动AUV路径跟踪控制[D].辽宁:大连海事大学,2020.

[11] 蒋云彪.欠驱动AUV自适应轨迹跟踪控制研究[D].辽宁:大连海事大学,2019.

[12] 王加荣.水下航行器设计及其航迹跟踪控制研究[D].绵阳: 西南科技大学,2021.

马洪潮, 戴晓强, 曾庆军, 夏楠, 郭雨青. 基于有限时间和状态观测器的双闭环AUV轨迹跟踪控制研究[J]. 电光与控制, 2022, 29(11): 17. MA Hongchao, DAI Xiaoqiang, ZENG Qingjun, XIA Nan, GUO Yuqing. Dual Closed-Loop AUV Trajectory Tracking Control Based on Finite Time and State Observer[J]. Electronics Optics & Control, 2022, 29(11): 17.

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