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文章基本信息

  • 标题:Learning vector quantization neural network–based model reference adaptive control method for intelligent lower-limb prosthesis
  • 本地全文:下载
  • 作者:Jia-Qiang Yang ; Lei Yang ; Yuliang Ma
  • 期刊名称:Advances in Mechanical Engineering
  • 印刷版ISSN:1687-8140
  • 电子版ISSN:1687-8140
  • 出版年度:2016
  • 卷号:8
  • 期号:4
  • DOI:10.1177/1687814016647354
  • 语种:English
  • 出版社:Sage Publications Ltd.
  • 摘要:This article focuses on the design of a control system for intelligent prostheses. Learning vector quantization neural network–based model reference adaptive control method is employed to implement real-time trajectory tracking and damp torque control of intelligent lower-limb prosthesis. The method is then analyzed and proposed. A model reference control system is first built with two learning vector quantization neural networks. One neural network is used for output prediction, and the other is used for input control. The angle information of the prosthetic knee joint is utilized to train these two neural networks with the given learning algorithm. The testing results of different movement patterns verify the effectiveness of the proposed method and its suitability for intelligent lower-limb prostheses.
  • 关键词:Intelligent lower-limb prosthesis; adaptive control; learning vector quantization neural network; reference model
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