Neural-Adaptive Sliding Mode Control of 4-SPS(PS) Type Parallel Manipulator

被引:3
|
作者
Zhu Dachang [1 ]
Zhang Guoxin [1 ]
Fang Yuefa [2 ]
机构
[1] Jiangxi Univ Sci & Technol, Coll Mech & Elect Control Engn Mech & Elect Contr, M&EC, Ganzhou, Jiangxi, Peoples R China
[2] JiaoTong Univ, Coll Mech & Elect Control Engn M & EC, Beijing, Peoples R China
关键词
parallel manipulator; sliding mode control (SMC); neural-adaptive control; least mean square (LMS) algorithm;
D O I
10.1109/ICARCV.2008.4795847
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a neural-adaptive sliding mode control for the tracking control of 4-SPS(PS) type parallel manipulator. The neural-adaptive controller is introduced to modify the coefficients of sliding manifold in sliding control strategy, which solve the problem that the equivalent control can not be obtained accurately because of the uncertain and fixed coefficients of sliding manifold and external disturbances of the system. So the controller can be designed without depend on fixed sliding manifold as general design method. Accordingly, it can be more effectively to solve the chattering in sliding mode control, The nonlinear controller, which guarantees the stability of the proposed control system based on Lyapunov stability theory, is also developed. Simulation results show that the control approach can decrease the tracking error, enhance the system's robustness and restrain the chattering effectively in the sliding mode control.
引用
收藏
页码:2055 / +
页数:2
相关论文
共 50 条
  • [31] Robust adaptive sliding mode control for industrial robot manipulator using fuzzy wavelet neural networks
    Vu Thi Yen
    Wang Yao Nan
    Pham Van Cuong
    Nguyen Xuan Quynh
    Vu Huu Thich
    International Journal of Control, Automation and Systems, 2017, 15 : 2930 - 2941
  • [32] Adaptive wave neural network nonsingular terminal sliding mode control for an underwater manipulator with force estimation
    Han, Lijun
    Tang, Guoyuan
    Zhou, Zengcheng
    Huang, Hui
    Xie, De
    TRANSACTIONS OF THE CANADIAN SOCIETY FOR MECHANICAL ENGINEERING, 2021, 45 (02) : 183 - 198
  • [33] Neural Network Adaptive Hierarchical Sliding Mode Control for the Trajectory Tracking of a Tendon-Driven Manipulator
    Zhang, Yudong
    He, Leiying
    Chen, Jianneng
    Yan, Bo
    Wu, Chuanyu
    CHINESE JOURNAL OF MECHANICAL ENGINEERING, 2025, 38 (01)
  • [34] Motion planning and adaptive neural sliding mode tracking control for positioning of uncertain planar underactuated manipulator
    Zhang, Pan
    Lai, Xuzhi
    Wang, Yawu
    Wu, Min
    NEUROCOMPUTING, 2019, 334 : 197 - 205
  • [35] Adaptive Nonsingular Fast Terminal Sliding mode Control of Robotic Manipulator Based Neural Network Approach
    Duc-Thien Tran
    Hoai-Vu-Anh Truong
    Kyoung Kwan Ahn
    International Journal of Precision Engineering and Manufacturing, 2021, 22 : 417 - 429
  • [36] Adaptive Nonsingular Fast Terminal Sliding mode Control of Robotic Manipulator Based Neural Network Approach
    Tran, Duc-Thien
    Truong, Hoai-Vu-Anh
    Ahn, Kyoung Kwan
    INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING, 2021, 22 (03) : 417 - 429
  • [37] Robust adaptive sliding mode control for industrial robot manipulator using fuzzy wavelet neural networks
    Vu Thi Yen
    Nan, Wang Yao
    Pham Van Cuong
    Nguyen Xuan Quynh
    Vu Huu Thich
    INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2017, 15 (06) : 2930 - 2941
  • [38] Manipulator trajectory tracking based on adaptive fuzzy sliding mode control
    Zhao, Haoyi
    Tao, Bo
    Ma, Ruyi
    Chen, Baojia
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2023, 35 (08):
  • [39] Adaptive sliding mode control of robotic manipulator based on reinforcement learning
    Ren, Ziwu
    Chen, Jie
    Miao, Yunxi
    Miao, Yujie
    Guo, Zibo
    Hu, Biao
    Lin, Rui
    ASIAN JOURNAL OF CONTROL, 2024, 26 (05) : 2703 - 2718
  • [40] Adaptive and sliding mode control of a mobile manipulator actuated by DC motors
    Karray, Amal
    Feki, Moez
    INTERNATIONAL JOURNAL OF AUTOMATION AND CONTROL, 2014, 8 (02) : 173 - 190