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It is difficult to obtain an accurate and complete mathematical model for the lower limb rehabilitative robot, and we will do some reasonable approximate treatments when building the model, so the external disturbance, parameter error, unmodeled dynamics and friction are ignored. These reasons will cause poor control performance. The neural network robust control for the lower limb rehabilitation...
Active exercise can improve the rehabilitation efficacy of the paralyzed patients, while we need to consider its safety. Impedance control takes the active compliance into account, providing a safe and comfortable training environment for the patients. However, the traditional impedance control has poor robustness, so it is urgent to enhance the adaptive capability of the system. This paper proposes...
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