Passivity-Based Learning Control for Torque and Cadence Tracking in Functional Electrical Stimulation (FES) Induced Cycling

Victor Duenas, Christian A. Cousin, Vahideh Ghanbari, Warren E. Dixon

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

10 Scopus citations

Abstract

This paper examines torque tracking accomplished by the activation of lower-limb muscles via Functional Electrical Stimulation (FES) and cadence regulation by an electric motor. Challenges arise from the fact that skeletal muscles evoke torque via FES in a time-varying, nonlinear, and delayed manner. A desired torque trajectory is constructed based on the crank position and determined by the knee joint torque transfer ratio (i.e., kinematic efficiency of the knee), which varies as a periodic function of the crank angle. To cope with this periodicity, a repetitive learning controller is developed to track the desired periodic torque trajectory by stimulating the muscle groups. Concurrently, a sliding-mode controller is designed for the electric motor to maintain cadence tracking throughout the entire crank cycle. A passivity-based analysis is developed to ensure stability of the torque and cadence closed-loop systems.

Original languageEnglish (US)
Title of host publication2018 Annual American Control Conference, ACC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3726-3731
Number of pages6
Volume2018-June
ISBN (Print)9781538654286
DOIs
StatePublished - Aug 9 2018
Externally publishedYes
Event2018 Annual American Control Conference, ACC 2018 - Milwauke, United States
Duration: Jun 27 2018Jun 29 2018

Other

Other2018 Annual American Control Conference, ACC 2018
CountryUnited States
CityMilwauke
Period6/27/186/29/18

Keywords

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

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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