Research on Coordinated Robotic Motion Control Based on Fuzzy Decoupling Method in Fluidic Environments

被引:0
|
作者
Zhang, Wei [1 ]
Chen, Haitian [1 ]
Chen, Tao [1 ]
Yan, Zheping [1 ]
Ren, Hongliang [2 ]
机构
[1] Harbin Engn Univ, Coll Automat, Harbin 150001, Heilongjiang, Peoples R China
[2] Natl Univ Singapore, Dept Bioengn, Singapore 117575, Singapore
基金
中国国家自然科学基金;
关键词
DOCKING;
D O I
10.1155/2014/820258
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The underwater recovery of autonomous underwater vehicles (AUV) is a process of 6-DOF motion control, which is related to characteristics with strong nonlinearity and coupling. In the recovery mission, the vehicle requires high level control accuracy. Considering an AUV called BSAV, this paper established a kinetic model to describe the motion of AUV in the horizontal plane, which consisted of nonlinear equations. On the basis of this model, the main coupling variables were analyzed during recovery. Aiming at the strong coupling problem between the heading control and sway motion, we designed a decoupling compensator based on the fuzzy theory and the decoupling theory. We analyzed to the rules of fuzzy compensation, the input and output membership functions of fuzzy compensator, through compose operation and clear operation of fuzzy reasoning, and obtained decoupling compensation quantity. Simulation results show that the fuzzy decoupling controller effectively reduces the overshoot of the system, and improves the control precision. Through the water tank experiments and analysis of experimental data, the effectiveness and feasibility of AUV recovery movement coordinated control based on fuzzy decoupling method are validated successful, and show that the fuzzy decoupling control method has a high practical value in the recovery mission.
引用
收藏
页数:10
相关论文
共 50 条
  • [11] Hybrid Fuzzy Decoupling Control for a Precision Maglev Motion System
    Zhou, Haibo
    Deng, Hua
    Duan, Ji'an
    IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2018, 23 (01) : 389 - 401
  • [12] Research on Coordinated Control Strategy of DFIG-ES System Based on Fuzzy Control
    Chen, Jianghong
    Yuan, Teng
    Li, Xuelian
    Li, Weiliang
    Wang, Ximu
    ENERGIES, 2023, 16 (12)
  • [13] The Unit Coordinated Control System Based on the Fuzzy Neural Network Inverse Control Method
    Wang, Qingli
    Jing, Yuanwei
    Wang, Lifu
    Kong, Zhi
    2008 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-11, 2008, : 5157 - +
  • [14] Research of arterial traffic coordinated fuzzy control model based on genetic algorithm
    Li, Ruimin
    Lu, Huapu
    WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS, 2006, : 8597 - +
  • [15] Coordinated motion and force control of multi-limbed robotic systems
    Dubowsky, S
    Sunada, C
    Mavroidis, C
    AUTONOMOUS ROBOTS, 1999, 6 (01) : 7 - 20
  • [16] Coordinated Motion and Force Control of Multi-Limbed Robotic Systems
    Steven Dubowsky
    Craig Sunada
    Constantinos Mavroidis
    Autonomous Robots, 1999, 6 : 7 - 20
  • [17] Research on Control Method of Current Loop Decoupling Based on Complex Vector
    Wu W.
    Ding X.
    Yan C.
    Yan, Caizhong (czyan_22@163.com), 1600, Chinese Society for Electrical Engineering (37): : 4184 - 4191
  • [18] Hybrid force/position control in workspace of robotic manipulator in uncertain environments based on adaptive fuzzy control
    Wang, Ziling
    Zou, Lai
    Su, Xiaojie
    Luo, Guoyue
    Li, Rui
    Huang, Yun
    Robotics and Autonomous Systems, 2021, 145
  • [19] Hybrid force/position control in workspace of robotic manipulator in uncertain environments based on adaptive fuzzy control
    Wang, Ziling
    Zou, Lai
    Su, Xiaojie
    Luo, Guoyue
    Li, Rui
    Huang, Yun
    ROBOTICS AND AUTONOMOUS SYSTEMS, 2021, 145
  • [20] Research on a Multi-Motor Coordinated Control Strategy Based on Fuzzy Ring Coupling Control
    Yu, Guoyan
    Sun, Jun
    Wu, Zhenlu
    Liu, Haochun
    Ji, Wenchao
    2020 CHINESE AUTOMATION CONGRESS (CAC 2020), 2020, : 7068 - 7072