Adaptive control for intelligent lower limb prosthesis based on
neural network
MA Yu-liang1, XU Wen-liang1, MENG Ming1, LUO Zhi-zeng1, YANG Jia-qiang2
1. School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China; 2. College of Electrical Engineering,
Zhejiang University, Hangzhou 310027, China
The knee joint of lower limb prosthesis is a damp system with high nonlinearity, timevarying and strong coupling, and the traditional control method can hardly achieve good performance. Aimed at the problem, a neural network (NN)based model reference adaptive control method was proposed based on the learning vector quantization (LVQ) neural network. Based on an appropriate reference model and an adaptive algorithm, the current control variable was calculated by using the error between the reference model output and the actual system output in order to control the intelligent lowerlimb prosthesis and achieve the adaptive control. The method does not require the transformation of performance criteria, and is fast and easy to implement. Simulation results showed the validity of the method.
MA Yu-Liang, XU Wen-Liang, MENG Meng, LUO Zhi-Ceng, YANG Jia-Jiang. Adaptive control for intelligent lower limb prosthesis based on
neural network. J4, 2010, 44(7): 1373-1376.
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