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Torque and cadence tracking in functional electrical stimulation induced cycling using passivity-based spatial repetitive learning control

https://doi.org/10.1016/j.automatica.2020.108852

Duenas, Victor H.; Cousin, Christian A.; Ghanbari, Vahideh; Fox, Emily J.; Dixon, Warren E. (May 2020, Automatica)
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Passivity-Based Iterative Learning Control for Cycling Induced by Functional Electrical Stimulation With Electric Motor Assistance

https://doi.org/10.1109/TCST.2018.2854773

Ghanbari, Vahideh; Duenas, Victor H.; Antsaklis, Panos J.; Dixon, Warren E. (September 2019, IEEE Transactions on Control Systems Technology)

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

https://doi.org/10.23919/ACC.2018.8431421

Duenas, Victor H.; Cousin, Christian A.; Ghanbari, Vahideh; Dixon, Warren E. (June 2018, American Control Conference)

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.
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