Nonlinear model predictive control of functional electrical stimulation

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• 作者：Nicholas Kirsch ^{nak65@pitt.edu} ; Naji Alibeji ^{naa33@pitt.edu} ; Nitin Sharma ; ^{nis62@pitt.edu}
• 关键词：Functional electrical stimulation ; Nonlinear model predictive control ; Muscle parameter identification ; Rehabilitation engineering ; Gradient projection algorithm
• 刊名：Control Engineering Practice
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：58
• 期：Complete
• 页码：319-331
• 全文大小：3800 K
• 卷排序：58

文摘

Minimizing the amount of electrical stimulation can potentially mitigate the adverse effects of muscle fatigue during functional electrical stimulation (FES) induced limb movements. A gradient projection-based model predictive controller is presented for optimal control of a knee extension elicited via FES. A control Lyapunov function was used as a terminal cost to ensure stability of the model predictive control. The controller validation results show that the algorithm can be implemented in real-time with a steady-state RMS error of less than 2°. The experiments also show that the controller follows step changes in desired angles and is robust to external disturbances.