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Neural network based global adaptive dynamic surface tracking control for robot manipulators

  • Tao Teng
  • , Chenguang Yang
  • , Bin Xu
  • , Zhijun Li
  • South China University of Technology
  • Swansea University
  • Northwestern Polytechnical University Xian

科研成果: 书/报告/会议事项章节会议稿件同行评审

5 引用 (Scopus)

摘要

A neural network empowered dynamic surface control (DSC) technique is addressed for robot manipulators system with unknown dynamics. In comparison to the conventional adaptive neural control algorithms, which could guarantee semi-globally uniformly ultimate boundedness (SGUUB) only when neural approximation keeps effective, the scheme designed in this paper ensures globally uniformly ultimately bounded (GUUB) stability by integrating a switching mechanism which incorporates an additional robust controller to drag the transient state variables back when they go beyond the neural approximation region. Simulation studies on 2-joint robot manipulator have been carried out to validate the designed controller has excellent performance.

源语言英语
主期刊名ICARM 2016 - 2016 International Conference on Advanced Robotics and Mechatronics
出版商Institute of Electrical and Electronics Engineers Inc.
20-25
页数6
ISBN(电子版)9781509033645
DOI
出版状态已出版 - 21 10月 2016
已对外发布
活动2016 International Conference on Advanced Robotics and Mechatronics, ICARM 2016 - Macau, 中国
期限: 18 8月 201620 8月 2016

出版系列

姓名ICARM 2016 - 2016 International Conference on Advanced Robotics and Mechatronics

会议

会议2016 International Conference on Advanced Robotics and Mechatronics, ICARM 2016
国家/地区中国
Macau
时期18/08/1620/08/16

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