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Title: Passivity-Based Learning Control for Torque and Cadence Tracking in Functional Electrical Stimulation (FES) Induced Cycling
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.  more » « less
Award ID(s):
1762829
NSF-PAR ID:
10137805
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
American Control Conference
Page Range / eLocation ID:
3726 to 3731
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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