Functional electrical stimulation induced cycling using repetitive learning control

Victor H. Duenas, Christian A. Cousin, Anup Parikh, Warren E. Dixon

Research output: Chapter in Book/Entry/PoemConference contribution

8 Scopus citations

Abstract

Cycling induced by functional electrical stimulation (FES) of the lower limb muscles is a common rehabilitative treatment. In this paper, a repetitive learning controller (RLC) is developed for cadence tracking during stationary FES-cycling. The RLC is developed for an uncertain, nonlinear cycle-rider system with autonomous state-dependent switching. The stimulation pattern switches across different muscle groups based on the joint effectiveness to produce torque during different regions of the crank cycle. An electric motor provides assistance in the regions of the crank cycle where the activation of the muscle groups yields low torque production. The developed RLC provides asymptotic cadence tracking despite the presence of unknown, time-varying, bounded disturbances. A Lyapunov-like stability analysis is implemented to generate the learning feedforward term and exploits a recently developed LaSalle-Yoshizawa corollary for nonsmooth systems.

Original languageEnglish (US)
Title of host publication2016 IEEE 55th Conference on Decision and Control, CDC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2190-2195
Number of pages6
ISBN (Electronic)9781509018376
DOIs
StatePublished - Dec 27 2016
Externally publishedYes
Event55th IEEE Conference on Decision and Control, CDC 2016 - Las Vegas, United States
Duration: Dec 12 2016Dec 14 2016

Publication series

Name2016 IEEE 55th Conference on Decision and Control, CDC 2016

Other

Other55th IEEE Conference on Decision and Control, CDC 2016
Country/TerritoryUnited States
CityLas Vegas
Period12/12/1612/14/16

Keywords

  • FES-Cycling
  • Functional Electrical Stimulation (FES)
  • Repetitive Learning Control (RLC)

ASJC Scopus subject areas

  • Artificial Intelligence
  • Decision Sciences (miscellaneous)
  • Control and Optimization

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