Abstract
In order to adapt to the personalized parameters and to the change of tempo in user’s lower limb prosthesis, taking these factors such as nonlinear model and parameter uncertainty of human prosthetic system into consideration, adaptive iterative learning controller has been designed to implement imputation control on it. First, the dynamic model of lower limb prosthesis is created. Then, adaptive iterative learning controller is designed to implement imputation control on it, using Lyapunov function method to prove the stability and convergence of tracking error. Finally, the knee trajectory simulation results are obtained. The final results show that the designed controller has excellent tracking results on the lower limb prosthetic knee.
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Acknowledgments
The authors would like to acknowledge the financial support from the Zhejiang Provincial Natural Science Foundation of Chin (Grant No. LY14F030023), and the National Natural Science Foundation of China (Grant No. 6137202361201300, 61201302, 61172134), and the Construction of Postgraduate Brand Course of Hangzhou Dianzi University (Grant No. PPKC2013YB006).
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Ma, Yl., Ding, Xh., Meng, M., She, Qs. (2015). Experimental Study on Adaptive Iterative Control for Lower Limb Prostheses. In: Deng, Z., Li, H. (eds) Proceedings of the 2015 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 337. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46463-2_45
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DOI: https://doi.org/10.1007/978-3-662-46463-2_45
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