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《第36届中国控制会议论文集(C)》2017年
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Neural Network Control of Lower Limb Rehabilitation Exoskeleton with Repetitive Motion

Deqing Huang  Lei Ma  Yong Yang  
【摘要】:This paper addresses neural network(NN) control of a lower limb exoskeleton for rehabilitation.Both the interaction between human and exoskeleton and external disturbances are considered.The controller is developed based on a combined scheme of repetitive learning control(RLC) and neural networks(NN),where RLC is used to learn periodic uncertainties(the interaction between human and exoskeleton) attribute to the repetitive motion of the exoskeleton leg,and NN is adopted to approximate all the external disturbances.Stabilities of the controllers are proved rigorously in a Lyapunov way.Simulations are worked out to illustrate the performance of the proposed control schemes.
【作者单位】:Institute of Systems Science and Technology,Southwest Jiaotong University
【基金】:supported by National Natural Science Foundation(NNSF) of China under Grant 61640310
【分类号】:R496;TP183
【正文快照】:
1Introduction Stroke patients often have to perform a large number of training during their rehabilitation therapy.In traditional assisted training,physiotherapists usually help patients to perform rehabilitation therapy manually[1].This leads to some

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