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Prescribed-Time Control of Flexible Joint Robotic Based on Neural Network

  • Beijing Institute of Technology
  • Ltd.
  • China North Artificial Intelligence & Innovation Research Institute
  • Collective Intelligence & Collaboration Laboratory

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

This paper proposes a neural network (NN) based adaptive prescribed-time sliding mode controller for flexible joint robotic (FJR) manipulators. By employing the singular perturbation technique, the original high-order system is decomposed into two lower-order subsystems. An NN is employed to estimate uncertainties within the FJR system, trained using a parameter identification algorithm (PIA). Subsequently, a prescribed-time sliding mode controller is developed for each subsystem to ensure that the tracking error converges within a predefined time and follows a given reference trajectory. The stability of the prescribed-time controller is rigorously established using Lyapunov analysis. Simulation and comparative experiments validate the effectiveness and superiority of the proposed method.

源语言英语
主期刊名Neuromorphic Computing - 4th International Conference, ICNC 2025, Revised Selected Papers
编辑Chuandong Li, Qi Zhou, Hongjing Liang, Jingang Lai, Bin Li, Kaibo Shi
出版商Springer Science and Business Media Deutschland GmbH
220-230
页数11
ISBN(印刷版)9789819215980
DOI
出版状态已出版 - 2026
已对外发布
活动4th International Conference on Neuromorphic Computing, ICNC 2025 - Chengdu, 中国
期限: 12 12月 202514 12月 2025

出版系列

姓名Communications in Computer and Information Science
2946 CCIS
ISSN(印刷版)1865-0929
ISSN(电子版)1865-0937

会议

会议4th International Conference on Neuromorphic Computing, ICNC 2025
国家/地区中国
Chengdu
时期12/12/2514/12/25

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