Robust Control of Functional Neuromuscular Stimulation System by Discrete-Time Iterative Learning

  • Huifang Dou
  • Zhaoying Zhou
  • Yangquan Chen
  • Jian-Xin Xu
  • James J. Abbas
Chapter

Abstract

High-order discrete-time P-type iterative learning controller (ILC) is proposed for the robust tracking control of the functional neuromuscular stimulation (FNS) systems, i.e., control of the electrical stimulation of human limb stimulation of the human limb which is no longer under voluntary control by the Central Nervous System (CNS). Control input saturation, which represents the maximum allowable stimulation pulse width (PW), is considered. A detailed musculoskeletal model is given for the simulation studies. The effectiveness of the proposed control scheme is demonstrated by simulation results. Some experimental results are presented. Finally, some of the theoretical challenges are introduced to stimulate further theoretic investigation in learning control of FNS systems.

functional neuromuscular stimulation (FNS) some theoretical challenges

Keywords

Tracking Error Muscle Fatigue Feedback Controller Iterative Learning Iterative Learn Control 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer Science+Business Media New York 1998

Authors and Affiliations

  • Huifang Dou
    • 1
  • Zhaoying Zhou
    • 1
  • Yangquan Chen
    • 2
  • Jian-Xin Xu
    • 2
  • James J. Abbas
    • 3
  1. 1.Dept. of Precision Instrument and MechanologyTsinghua UniversityBeijingChina
  2. 2.Dept. of Electrical EngineeringNational University of SingaporeSingapore
  3. 3.Center for Biomedical EngineeringUniversity of KentuckyLexingtonUSA

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