Please wait a minute...
浙江大学学报(工学版)  2018, Vol. 52 Issue (8): 1467-1473    DOI: 10.3785/j.issn.1008-973X.2018.08.005
计算机技术     
基于动态反馈的AUV水平面路径跟踪控制
赵杰梅1, 胡忠辉2
1. 武汉轻工大学 数学与计算机学院, 湖北 武汉 430023;
2. 中船重工第709研究所, 湖北 武汉 430074
Path following control of AUV in horizontal plane based on dynamic feedback control
ZHAO Jie-mei1, HU Zhong-hui2
1. School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan 430023, China;
2. 709 th Research Institute of China Shipbuilding Industry Corporation, Wuhan 430074, China
 全文: PDF(1990 KB)   HTML
摘要:

针对离散自治水下机器人水平面的路径跟踪控制问题,利用水下机器人的位置和姿态角量测信息,提出神经网络自适应输出反馈控制器.所设计的控制器包括3部分,镇定水下机器人动态系统线性部分的动态反馈控制器;神经网络控制器,用来补偿水下机器人受到环境干扰引起的水动力系数变化的不确定非线性结构;补偿环境扰动和神经网络带来的重构误差的鲁棒控制器.基于离散非线性系统理论,对水下机器人水平面跟踪误差系统进行分析,得到系统的跟踪误差最终一致有界.所提出的控制方法具有对模型精确度要求低的优点,利用INFANTE水下机器人模型进行仿真分析验证了提出的控制算法的有效性.

Abstract:

Aiming at the path following control in horizontal plane of discrete-time autonomous underwater vehicle (AUV), a neural network adaptive output feedback controller was proposed using the information of AUV position and attitude angle. The controller consisted of three parts:dynamic feedback controller which was used to stabilize the linear part of AUV dynamic system; neural network controller which was used to compensate the AUV nonlinear uncertainty induced by hydrodynamic coefficients; and robust controller which was used to compensate the reconstructive error of neural network and environmental disturbances. Based on the theory of discrete-time nonlinear systems, the AUV tracking error system in horizontal plane was analyzed and proved to be uniformly ultimately bounded. The proposed control algorithm required low accuracy of the system model. The model of INFANTE AUV was taken to verify the effectiveness of the proposed control algorithm by simulation.

收稿日期: 2017-06-02 出版日期: 2018-08-23
CLC:  TP273  
基金资助:

国家自然科学基金资助项目(61603109);湖北省自然科学基金资助项目(2016CFB273)

作者简介: 赵杰梅(1984-),女,讲师,从事水下机器人及非线性控制研究.orcid.org/0000-0002-4147-1883.E-mail:jiemeizhao@163.com
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
作者相关文章  

引用本文:

赵杰梅, 胡忠辉. 基于动态反馈的AUV水平面路径跟踪控制[J]. 浙江大学学报(工学版), 2018, 52(8): 1467-1473.

ZHAO Jie-mei, HU Zhong-hui. Path following control of AUV in horizontal plane based on dynamic feedback control. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2018, 52(8): 1467-1473.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2018.08.005        http://www.zjujournals.com/eng/CN/Y2018/V52/I8/1467

[1] LAPIERRE L. Robust diving control of an AUV[J]. Ocean Engineering, 2009, 36(1):92-104.
[2] 徐玉如, 肖坤. 智能海洋机器人技术进展[J]. 自动化学报, 2007, 33(5):518-521 XU Yu-ru, XIAO Kun. Technology development of autonomous ocean vehicle[J]. Acta Automatica Sinica, 2007, 33(5):518-521
[3] 史剑光, 李德骏, 杨灿军, 等. 水下自主机器人接驳碰撞过程分析[J]. 浙江大学学报:工学版, 2015, 49(3):497-504 SHI Jian-guang, LI De-jun, YANG Can-jun, et al. Impact analysis during docking process of autonomous underwater vehicle[J]. Journal of Zhejiang University: Engineering Science, 2015, 49(3):497-504
[4] AGUIAR A, HESPANHA J. Trajectory-tracking and path-following of underactuated autonomous vehicles with parametric modeling uncertainty[J]. IEEE Tran sactions on Automatic Control, 2007, 52(8):1362-1379.
[5] 魏清平, 王硕, 董翔, 等. 一种仿生水下机器人的设计与动力学分析[J]. 自动化学报, 2013, 39(8):1330-1338 WEI Qing-ping, WANG Suo, DONG Xiang, et al. Design and kinetic analysis of a biomimetic underwater vehicle with two undulating long-fins[J]. Acta Automatica Sinica, 2013, 39(8):1330-1338
[6] LIANG X, WAN L, BLAKE J, et al. Path following of an underactuated AUV based on fuzzy backstepping sliding mode control[J]. International Journal of Advanced Robotic Systems, 2016, 13(122):1-11.
[7] PEYMANI E, FOSSEN T I. Path following of underwater robots using Lagrange multipliers[J]. Robotics and Autonomous Systems, 2015, 67:44-52.
[8] 初亮, 李天骄, 孙成伟. 面向再生制动优化的电动车自适应巡航控制策略[J]. 浙江大学学报:工学版, 2017, 51(8):1596-1602 CHU Liang, LI Tian-jiao, SUN Cheng-wei. Research on adaptive cruise control strategy for electric vehicle based on optimization of regenerative braking[J]. Journal of Zhejiang University:Engineering Science, 2017, 51(8):1596-1602
[9] 唐志国, 李元春, 刘木林. 机械臂协调操作柔性负载鲁棒神经网络控制[J]. 浙江大学学报:工学版, 2010, 44(7):1394-1399 TANG Zhi-guo, LI Yuan-chun, LIU Mu-lin. Robust neural network control of dual-manipulator cooperative system handling flexible payload[J]. Journal of Zhejiang University:Engineering Science, 2010, 44(7):1394-1399
[10] ZHAO J. NN-adaptive predictive control for a class of discrete-time nonlinear systems with input-delay[J]. Neurocomputing, 2016, 173:1832-1838.
[11] 程鹏飞, 吴成富. 单侧机翼损伤飞机的神经网络自适应鲁棒非线性控制[J]. 系统工程与电子技术, 2016, 38(3):607-617 CHENG Peng-fei, WU Cheng-fu. Neural network based robust adaptive nonlinear control for aircraft under one side of wing loss[J]. Systems Engineering and Electronics, 2016, 38(3):607-617
[12] CUI R, YANG C, LI Y, et al. Adaptive neural network control of AUVs with control input nonlinearities using reinforcement learning[J]. IEEE transactions on Systems, Man, and Cybernetics:Systems, 2017, 47(6):1019-1029.
[13] LIU Y, TONG S. Optimal control-based adaptive NN design for a class of nonlinear discrete-time block-triangular systems[J]. IEEE Transactions on Cybernetics, 2016, 46(11):2670-2680.
[14] QI X. Adaptive coordinated tracking control of multiple autonomous underwater vehicles[J]. Ocean Engineering, 2014, 91:84-90.
[15] ZHANG L, QI X, PANG Y. Adaptive output feedback control based on DRFNN for AUV[J]. Ocean Engineering, 2009, 36(9):716-722.
[16] PARK B. Adaptive formation control of underactuated autonomous underwater vehicles[J]. Ocean Engineering, 2015, 96:1-7.
[17] 张利军, 齐雪, 赵杰梅, 等. 垂直面欠驱动自治水下机器人定深问题的自适应输出反馈控制[J]. 控制理论与应用, 2012, 29(10):1371-1376 ZHANG Li-jun, QI Xue, ZHAO Jie-mei, et al. Depth-keeping control for autonomous underwater vehicle in vertical plane using adaptive output feedback controller[J]. Control Theory and Applications, 2012, 29(10):1371-1376
[18] SUBUDHI B, MUKHERJEE K, GHOSH S. A static output feedback control design for path following of autonomous underwater vehicle in vertical plane[J]. Ocean Engineering, 2013, 63:72-76.
[19] LI S, WANG X, ZHANG L. Finite-time output feedback tracking control for autonomous underwater vehicles[J]. IEEE Journal of Oceanic Engineering, 2015, 40(3):727-751.
[20] LIU S, WANG D, POH E. Output feedback control design for station keeping of AUVs under shallow water wave disturbances[J]. International Journal of Robust and Nonlinear Control, 2009, 19(13):1447-1470.
[21] PENG Z, WANG J. Output-feedback path-following control of autonomous underwater vehicles based on an extended state observer and projection neural networks[J]. IEEE Transactions on Systems, Man, and Cybernetics:Systems, 2018, 48(4):535-544.
[22] KUMAR R, KUMAR C, SEN D, et al. Discrete time-delay control of an autonomous underwater vehicle:theory and experimental results[J]. Ocean Engineering, 2009, 36(1):74-81.
[23] SANTOS O, ROMERO H, SALAZAR S, et al. Optimized discrete control law for quadrotor stabilization:experimental results[J]. Journal of Intelligent and Robotic Systems, 2016, 84(1-4):1-15.
[24] YU J, SHI P, DONG W, et al. Neural network-based adaptive dynamic surface control for permanent magnet synchronous motors[J]. IEEE Transactions on Neural Networks and Learning Systems, 2015, 26(3):640-645.
[25] HE W, CHEN Y, YIN Z. Adaptive neural network control of an uncertain robot with full-state constraints[J]. IEEE Transactions on Cybernetics, 2016, 46(3):620-629.
[26] MA J, GE S S, ZHENG Z, et al. Adaptive NN control of a class of nonlinear systems with asymmetric saturation actuators[J]. IEEE Transactions on Neural Networks and Learning Systems, 2015, 26(7):1532-1538.

[1] 郑鹏远, 王针针, 相振东, 冯冬涵. 线性参数时变可测系统的混合反馈预测控制[J]. 浙江大学学报(工学版), 2018, 52(4): 703-709.
[2] 劳立明, 陈英龙, 赵玉刚, 周华. 跟踪微分器的等效线性分析及优化[J]. 浙江大学学报(工学版), 2018, 52(2): 224-232.
[3] 朱笑花, 王宁. cRNA布谷鸟搜索算法的桥式吊车PID控制[J]. 浙江大学学报(工学版), 2017, 51(7): 1397-1404.
[4] 朱上上, 罗仕鉴, 应放天, 何基. 支持产品视觉识别的产品族设计DNA[J]. J4, 2010, 44(4): 715-721.
[5] 罗仕鉴, 翁建广, 陈实, 等. 基于情境的产品族设计风格DNA[J]. J4, 2009, 43(6): 1112-1117.
[6] 侯鑫, 李平, 韩波, 等. 小型无人直升机分层混杂控制系统[J]. J4, 2009, 43(5): 796-800.
[7] 王晔, 刘山. 期望轨迹可变的非线性时变系统迭代学习控制[J]. J4, 2009, 43(5): 839-843.