Functional electrical stimulation system of elbow joint based on iterative learning control
Chen Shengqin1,2, Li Yurong1,2, Chen Jun1,2, Chen Jianguo1,2
1. College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350116; 2. Fujian Key Laboratory of Medical Instrumentation & Pharmaceutical Technology, Fuzhou University, Fuzhou 350116;
Abstract：Forthe rehabilitation and reconstructing motor function of upper limb in patients with limb dysfunction, a functional electrical stimulation (FES) system for elbow joint was designed. An elbow joint movement model using dynamic neural network was established. According to the nonlinearity of the model and the repeatability of the elbow joint trajectory, iterative learning control algorithm is used to design the controller of the FES system, and the FES system for the precise control of elbow joint angles is implemented. After 10 iterations, the maximum error between the actual trajectory and the desired trajectory is 0.348°, the average relative error is 0.32%, and the root mean square error is 0.245°. The results show that the FES system based on the ILC algorithm can realize the accurate control of the elbow joint movement stimulated by electric stimulation, and has certain guiding significance for the study of the FES system for elbow rehabilitation.
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2018, Vol. 19 
