非线性迭代学习算法在机器人上肢康复中的应用

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.

Nonlinear iterative learning algorithm and its application in upper limb rehabilitation

For the nonlinear and uncertainty problems in the upper limb rehabilitation robot trajectory tracking control, combining the characteristic of repetitive execution of the rehabilitation robot system and the properties of iterative learning control, a nonlinear iterative learning control algorithm is proposed. This algorithm improves the commonly used linear robot dynamics control, so that the good control quality is obtained under the condition that the model information is not accurate and only the position feedback can be measured. The Lyapunov stability theory and LaSalle invariance principle are applied to prove the global asymptotic stability of the closed-loop system. The simulation results show that the proposed nonlinear iterative learning control has good control performance.