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针对上肢康复机器人轨迹跟踪控制中存在的患者痉挛扰动非线性及不确定性问题,结合康复机器人系统执行具有重复性的特点以及迭代学习算法特有的性质,提出一种非线性迭代学习控制算法,改进了机器人常用的线性动力学控制系统,使得在模型信息不精确以及只有角度信息可测的情况下,也能获得良好的轨迹跟踪性能;应用Lyapunov稳定性理论和LaSalle不变性原理证明了闭环系统的全局渐近稳定性.仿真结果表明,所提出的非线性迭代学习控制具有良好的控制性能.
Considering the non-linearity and uncertainty of the patient’s spasticity perturbation in trajectory tracking control of upper limb rehabilitation robot, combined with the repetitive characteristics of the rehabilitation robot system and the peculiar properties of iterative learning algorithm, a nonlinear iterative learning control algorithm is proposed to improve The linear dynamics control system commonly used in robots makes the trajectory tracking performance good even when the model information is inaccurate and only the angle information is measurable. By using Lyapunov stability theory and LaSalle invariance theory, it is proved that the closed-loop system Global asymptotic stability.The simulation results show that the proposed nonlinear iterative learning control has good control performance.