下肢外骨骼助力机构及滑模步态轨迹跟踪控制方法

Lower Extremity Exoskeleton Assisted Mechanism and Sliding Mode Gait Tracking Control Method

摘要: 构建高精度下肢外骨骼步态方法有助于下肢康复效果的提升。针对下肢外骨骼辅助残疾患者康复治疗时电机跟踪精度不足的问题，基于下肢结构建立动力学模型，并设计线性执行机构驱动的外骨骼结构模型。为提高步态输出精度，减小外骨骼工作时外部干扰的影响，设计了一种结合非线性干扰观测器(Nonlinear Disturbance Observer, NDO)的滑模(Sliding Mode Control, SMC)控制方法，并使用优化器对控制模型参数全局寻优，获得最优反演滑模控制律参数。通过比较SMC与NDO-SMC在引入干扰信号下的跟踪精度，发现NDO方法可有效减少外部干扰的影响，使跟踪精度提升31%；比较SMC与AO-SMC控制器的轨迹跟踪误差，优化器相较于遗传算法在控制算法参数收敛速度方面有较大提升，并使步态轨迹跟踪精度提升了63%。

Abstract: The construction of high precision lower limb exoskeleton gait method is helpful to improve the lower limb rehabilitation effect. Aiming at the problem of insufficient motor tracking accuracy in the rehabilitation treatment of patients with disabilities assisted by lower limb exoskeleton, a dy-namic model was established based on lower limb structure, and a linear actuator driven exoskele-ton structure model was designed. In order to improve the accuracy of gait output and reduce the influence of external Disturbance in exoskeleton operation, a Sliding Mode Control (SMC) method combining Nonlinear Disturbance Observer (NDO) is designed. The optimizer is used to globally op-timize the parameters of the control model to obtain the optimal inversion sliding mode control law parameters. By comparing the tracking accuracy of SMC and NDO-SMC in the presence of interfer-ence signals, it is found that the NDO method can effectively reduce the influence of external inter-ference and improve the tracking accuracy by 31%. Comparing the trajectory tracking errors of SMC and AO-SMC controller, compared with genetic algorithm, the optimizer greatly improves the con-vergence speed of control algorithm parameters, and improves the gait trajectory tracking accuracy by 63%.