• 中国科技核心期刊
  • Scopus收录期刊
  • DOAJ收录期刊
  • JST收录期刊
  • Euro Pub收录期刊
WANG Ming-liang, LI De-long, LIN Yang, ZHU Xing-hua, JIA Song-li. AUV Rudder Angle Decoupling Method Based on Energy Optimization[J]. Journal of Unmanned Undersea Systems, 2019, 27(3): 319-326. doi: 10.11993/j.issn.2096-3920.2019.03.013
Citation: WANG Ming-liang, LI De-long, LIN Yang, ZHU Xing-hua, JIA Song-li. AUV Rudder Angle Decoupling Method Based on Energy Optimization[J]. Journal of Unmanned Undersea Systems, 2019, 27(3): 319-326. doi: 10.11993/j.issn.2096-3920.2019.03.013

AUV Rudder Angle Decoupling Method Based on Energy Optimization

doi: 10.11993/j.issn.2096-3920.2019.03.013
  • Received Date: 2018-12-06
  • Rev Recd Date: 2019-01-04
  • Publish Date: 2019-06-30
  • During the steering of tail rudder linkage of an underactuated autonomous undersea vehicle(AUV), the rolling attitude will result in the coupling of controls in horizontal and vertical planes. Focusing on the navigation mission of the AUV with low restoring moment, single propeller and variable loads, this paper proposes a new rudder angle decoupling method with energy reuse based on the known roll angle, in which global optimal utilization of the energy generated by rolling attitude is taken into account. A neural network algorithm is used in the decoupling method to optimize the decoupling parameters, thus reducing the working stroke of the actuators and enhancing the utilization of global energy. Numerical simulation result coincides with the theory analysis, validating the feasibility of the proposed method. Results from sea trial indicate that the proposed method can effectively reduce the steering stroke of the actuators and power consumption.

     

  • loading
  • [1]
    王芳荣, 阚如文, 王昕, 等. 无人水下航行器PID神经网络解耦控制[J]. 吉林大学学报(工学版), 2012, 42(1): 387- 391.

    Wang fang-rong, Han Ru-wen, Wang xin, et al. PID Neural Network Decoupling Control of Unmanned Underwater Vehicle[J]. Journal of Jilin University (Engineering and Technology Edition), 2012, 42(1): 387-391.
    [2]
    魏延辉, 周卫祥, 贾献强, 等. AUV模型解耦水平运动多控制器联合控制[J]. 华中科技大学学报(自然科学版), 2016, 44(4): 37-42.

    Wei Yan-hui, Zhou Wei-xiang, Jia Xian-qiang, et al. Model Decoupling and Multi-controller Joint Control of Horizontal Movement for AUV[J]. Journal of Huazhong University of Science and Technology(Nature Science Edition), 2016, 44 (4): 37-42.
    [3]
    张秦南, 宋喜发, 吕瑞, 等. 大机动下鱼雷滚动控制规律设计[J]. 鱼雷技术, 2012, 20(1): 47-50.

    Zhang Qin-nan, Song Xi-fa, Lü Rui, et al. Design of Control Law for Torpedo Rolling under Large Maneuvering Motion[J]. Torpedo Technology, 2012, 20(1): 47-50.
    [4]
    杨永鹏, 赵玉新, 郝燕玲, 等. AUV近水面悬浮解耦控制系统设计及仿真[J]. 系统工程与电子技术, 2012, 34(3): 572-576.

    Yang Yong-peng, Zhao Yu-xin, Hao Yan-ling, et al. Decoupling Control System for AUV Hovering Nearsurface[J]. Systems Engineering and Electronics, 2012, 34(3): 572-576.
    [5]
    宋晓茹, 宋保维, 雷志勇, 等. 基于RS-LSSVM的AUV耦合控制方法[J]. 西北工业大学学报, 2013, 31(4): 614-619.

    Song Xiao-ru, Song Bao-wei, Lei Zhi-yong, et al. A New Method of AUV Control Based on RS-LSSVM for Suppressing Inevitable but Overlooked Coupling[J]. Journal of Northwestern Polytechnical University, 2013, 31(4): 614-619.
    [6]
    蒋新松, 封锡盛, 王棣棠. 水下机器人[M]. 沈阳: 辽宁科学技术出版社, 2000: 252-256.
    [7]
    Hagan M T, Demuth H B, Beale M H. Neural Network Design(2nd Edition)[M]. Boston, MA, USA: Martin Hagan, 2014.
    [8]
    周焕银, 刘开周, 封锡盛. 基于神经网络的自主水下机器人动态反馈控制[J]. 电机与控制学报, 2011, 15(7): 87-93.

    Zhou Huan-yin, Liu Kai-zhou, Feng Xi-sheng. Dynamic Feedback Control Based on ANN Compensation Controller for AUV motions[J]. Electric Machines and Control, 2011, 15(7): 87-93.
    [9]
    Heemels W P M H, Donkers M C F. Model-based Periodic Event-triggered Control for Linear Systems[J]. Automatica, 2013, 49(3): 698-711.
    [10]
    Donkers M C F, Heemels W P M H. Output-Based Event-Triggered Control With Guaranteed L∞-Gain and Improved and Decentralized Event-Triggering[J]. IEEE Transactions on Atuomatic Control, 2012, 57(6): 1362-1376.
    [11]
    吴亚军, 毛昭勇. 小波神经网络多传感器信息融合在AUV深度测量中的应用[J]. 鱼雷技术, 2016, 24(4): 267-270.

    Wu Ya-jun, Mao Zhao-yong. Application of Multi-Sensor Information Fusion Based on Wavelet Neural Network to Depth Measurement for AUV[J]. Torpedo Technology, 2016, 24(4): 267-270.
    [12]
    夏国清, 汤莉. 基于动态神经网络的AUV航向自适应控制[J]. 船舶工程, 2009, 31(2): 46-49.

    Xia Guo-qing, Tang Li. AUV Heading Adaptive Control Based on The Dynamic Neural Network[J]. Ship Engineering, 2009, 31(2): 46-49.
    [13]
    郑荣, 马艳彤, 张斌, 等. 基于垂向推进方式的AUV低速近底稳定航行[J]. 机器人, 2016, 38(5): 588-592.

    Zheng Rong, Ma Yan-tong, Zhang Bin, et al. Stable Control for AUV’s Near-bottom and Low-speed Sailing Based on Vertical Thruster[J]. Robot, 2016, 38(5): 588-592.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article Views(532) PDF Downloads(288) Cited by()
    Proportional views
    Related
    Service
    Subscribe

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return