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Abstract
A high-order iterative learning controller (ILC) is proposed for the tracking control of an electrically stimulated human limb that is repeatedly required to perform a given task. The limb is actuated by the muscles, which are out of the control of the central nerve systems (CNS), through functional electrical stimulation (FES) or functional neuromuscular stimulation (FNS). By using the proposed discrete-time high-order P-type ILC updating law and the PD-type feedback controller, it is shown that the proposed control strategy, which learns from repetitions, provides strong robustness in tracking control of the uncertain time-varying FES systems, which is essential for the adaptation and customization of FES applications. The effectiveness of the proposed control scheme is demonstrated by simulation results on a one-segment planar system. Some experimental results are also presented to validate the proposed control method. © 1999 Elsevier Science Ltd. All rights reserved.
Keywords
Discrete-time nonlinear systems, Functional neuromuscular stimulation, Input saturation, Iterative learning control, Nonlinear muscle models, Tracking control
Source Title
Control Engineering Practice
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Date
1999-03
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Type
Article