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针对上肢康复机器人主动康复训练过程中,存在不可预知的人机交互作用力和不确定的患者痉挛扰动问题,通过实时采集人机交互力,设计一种非线性滚动时域跟踪控制算法,并对该控制器的稳定性进行了分析.该控制器基于上肢康复机器人系统在每个采样时刻的线性化模型预测系统未来的动态,以人工免疫优化算法为滚动优化策略,不仅提高了系统的抗干扰性能,而且保证了系统在整个预测时域上能得到可行解.仿真研究表明了该控制器的有效性.
In the process of active rehabilitation training of upper limb rehabilitation robot, there are unpredictable human-computer interaction and uncertainties in patients with spasm disturbance. By collecting human-computer interaction in real time, a non-linear rolling time-domain tracking control algorithm is designed. The stability of the controller is analyzed.The controller predicts the future dynamic of the system based on the linearized model of the upper limb rehabilitation robot system at each sampling time.The artificial immune optimization algorithm is a rolling optimization strategy which not only improves the system’s anti-interference But also ensures that the system can get a feasible solution over the entire predicted time domain.The simulation results show the effectiveness of this controller.