TY - GEN
T1 - Passivity-Based Learning Control for Torque and Cadence Tracking in Functional Electrical Stimulation (FES) Induced Cycling
AU - Duenas, Victor H.
AU - Cousin, Christian A.
AU - Ghanbari, Vahideh
AU - Dixon, Warren E.
N1 - Funding Information:
1. Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville FL 32611-6250, USA. Email: {vhduenas, ccousin, wdixon}@ufl.edu, 2. Department of Electrical Engineering, at the University of Notre Dame, Notre Dame, IN 46556, USA Email: {vghanbar}@nd.edu This research is supported in part by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE-1315138 and AFOSR award number FA9550-18-1-0109. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the sponsoring agency.
Publisher Copyright:
© 2018 AACC.
PY - 2018/8/9
Y1 - 2018/8/9
N2 - 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.
AB - 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.
KW - FES-Cycling
KW - Functional Electrical Stimulation (FES)
KW - Passivity-Based Control
KW - Repetitive Learning Control (RLC)
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U2 - 10.23919/ACC.2018.8431421
DO - 10.23919/ACC.2018.8431421
M3 - Conference contribution
AN - SCOPUS:85052569423
SN - 9781538654286
T3 - Proceedings of the American Control Conference
SP - 3726
EP - 3731
BT - 2018 Annual American Control Conference, ACC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 Annual American Control Conference, ACC 2018
Y2 - 27 June 2018 through 29 June 2018
ER -