期刊名称：International Journal of Advanced Robotic Systems
印刷版ISSN：1729-8806
电子版ISSN：1729-8814
出版年度：2016
卷号：13
期号：5
DOI：10.1177/1729881416662788
语种：English
出版社：SAGE Publications
摘要：This article presents a human–robot cooperation controller towards the lower extremity exoskeleton which aims to improve the tracking performance of the exoskeleton and reduce the human–robot interaction force. Radial basis function neural network is introduced to model the human–machine interaction which can better approximate the non-linear relationship than the general impedance model. A new method to calculate the inverse Jacobian matrix is presented. Compared to traditional damped least squares method, the novel method is proved to be able to avoid the orientation change of the velocity of the human–robot interaction point by the simulation result. This feature is very important in human–robot system. Then, an improved non-linear robust sliding mode controller is designed to promote the tracking performance considering system uncertainties and model errors, where a new non-linear integral sliding surface is given. The stability analysis of the proposed controller is performed using Lyapunov stability theory. Finally, the novel methods are applied to the swing leg control of the lower extremity exoskeleton, its effectiveness is validated by simulation and comparative experiments.
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