Iterative learning control strategy for functional neuromuscular stimulation

Huifang Dou, Zhaoying Zhou, Yangquan Chen, Jian Xin Xu, James Abbas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

An iterative learning controller (ILC) is proposed for the tracking control of functional neuromuscular stimulation (FNS) system performing the given task repeatedly. A P-type ILC updating law assisted by PD closed-loop controller is suggested for a simpler implementation. This kind of learning from repetitions control strategy supplies strong robustness in tracking control of uncertain time-varying FNS systems, which is essential for the adaptation and customization of FNS applications. Nonlinear muscle recruitment, linear muscle dynamics in force generation, and multiplicative nonlinear torque-angle and torque-velocity scaling factors are considered in the electrically stimulated muscle model for the simulation studies. An one-segment planar system with passive constraints on joint movement is taken as the skeletal model. Simulation results indicate that the control scheme of this paper is promising for FNS system control.

Original languageEnglish (US)
Title of host publicationAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
PublisherIEEE
Pages426-427
Number of pages2
Edition1
StatePublished - 1996
Externally publishedYes
EventProceedings of the 1996 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Part 2 (of 5) - Amsterdam, Neth
Duration: Oct 31 1996Nov 3 1996

Other

OtherProceedings of the 1996 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Part 2 (of 5)
CityAmsterdam, Neth
Period10/31/9611/3/96

ASJC Scopus subject areas

  • Bioengineering

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