上肢康复外骨骼机器人的模糊滑模导纳控制

为了辅助上肢运动功能障碍患者进行不同模式的康复训练，基于上肢康复外骨骼机器人系统，提出了一种模糊滑模导纳控制策略，实现训练过程的人机协调控制.首先，介绍了康复外骨骼的整体结构和实时控制平台.然后，分析了模糊滑模导纳控制算法的推导过程，并根据李亚普诺夫稳定性判据证明系统的稳定性.最后，在不同系统导纳参数条件下，分别进行被动训练模式和主动训练模式实验，并对比分析了实验过程中运动偏差、人机交互力以及肱二头肌表面肌电信号的变化特点.实验结果表明，选择合适的目标导纳模型可以优化康复训练强度与难度，提高人机交互柔顺性与患者参与度，满足不同瘫痪程度和康复进度患者的训练需求.

Fuzzy Sliding Mode Admittance Control of the Upper Limb Rehabilitation Exoskeleton Robot

With the aim of assisting the patients with upper limb motion impairment problem to perform different types of rehabilitation training, a fuzzy sliding mode admittance control strategy is developed to realize human-robot coordinated control during training process based on the upper limb rehabilitation exoskeleton robot system. Firstly, the overall structure of rehabilitation exoskeleton and the real-time control platform are introduced. Then, the derivation process of the fuzzy sliding mode admittance control algorithm is analyzed, and the system stability is demonstrated by Lyapunov stability criterion. Finally, the passive training mode experiment and active training mode experiment are carried out under different system admittance parameters. The changing characteristics of motion deviation, human-robot interaction force, and the surface electromyography signal of bicipital muscle during experiment process are analyzed and compared. The experimental results show that the intensity and difficulty of rehabilitation training can be optimized, the human-robot interactive compliance and the active participation of patient can be improved, and the requirements of the patients with different paralysis degrees and recovery process can be satisfied by selecting appropriate objective admittance model.