梁旭, 王卫群, 苏婷婷, 侯增广, 何广平, 任士鑫, 石伟国. 下肢康复机器人的主动柔顺自适应交互控制[J]. 机器人, 2021, 43(5): 547-556. DOI: 10.13973/j.cnki.robot.210029
引用本文: 梁旭, 王卫群, 苏婷婷, 侯增广, 何广平, 任士鑫, 石伟国. 下肢康复机器人的主动柔顺自适应交互控制[J]. 机器人, 2021, 43(5): 547-556. DOI: 10.13973/j.cnki.robot.210029
LIANG Xu, WANG Weiqun, SU Tingting, HOU Zengguang, HE Guangping, REN Shixin, SHI Weiguo. Active Compliant and Adaptive Interaction Control for a Lower Limb Rehabilitation Robot[J]. ROBOT, 2021, 43(5): 547-556. DOI: 10.13973/j.cnki.robot.210029
Citation: LIANG Xu, WANG Weiqun, SU Tingting, HOU Zengguang, HE Guangping, REN Shixin, SHI Weiguo. Active Compliant and Adaptive Interaction Control for a Lower Limb Rehabilitation Robot[J]. ROBOT, 2021, 43(5): 547-556. DOI: 10.13973/j.cnki.robot.210029

下肢康复机器人的主动柔顺自适应交互控制

Active Compliant and Adaptive Interaction Control for a Lower Limb Rehabilitation Robot

  • 摘要: 为了更好地给患者提供稳定、舒适且具备主动柔顺性的康复训练环境,提出一种基于阻抗参数自适应调节的下肢康复机器人主动柔顺交互控制方案,该方案由外环的阻抗参数调节和内环的轨迹跟踪两部分构成.首先,针对康复训练过程中人体阻抗参数动态变化的问题,提出了模糊自适应阻抗参数调节器,将人机交互作用力、位置误差与速度误差作为输入,并采用模糊推理实时调整阻尼系数与刚度系数,实现对人体阻抗的自适应.其次,设计了间接自适应模糊控制器,合理构造模糊系统逼近未知非线性系统,对反映患者运动意图的设定轨迹进行稳定跟踪,利用李亚普诺夫分析方法证明了系统的稳定性.最后,通过仿真实验将本文方法与一般的固定期望阻抗参数方法对比,结果表明本文方法下的髋、膝关节轨迹的最大偏差分别降低53.43%和66.87%,验证了所提方法的可行性与有效性.

     

    Abstract: In order to provide patients with a stable, comfortable and active compliant rehabilitation training environment, an active compliant interactive control scheme for a lower limb rehabilitation robot based on adaptive adjustment of impedance parameters is proposed. It consists of two parts:the outer loop for impedance parameter adjustment and the inner loop for trajectory tracking. Firstly, a fuzzy adaptive impedance parameter adjuster is proposed to solve the problem caused by the dynamic change of impedance parameters of human body during rehabilitation training. It takes the human-robot interaction force, the position error and the speed error as inputs, and uses the fuzzy inference to adjust the damping and stiffness coefficients in real time to realize the self-adaptation to human body impedance. Secondly, an indirect adaptive fuzzy controller is designed, in which the fuzzy system is reasonably constructed to approximate the unknown nonlinear system, and the set trajectory reflecting the patient's motion intention is tracked stably. The system stability is proved by Lyapunov method. Finally, the simulation results show that the maximum deviations of the hip and knee trajectories under the proposed method are reduced by 53.43% and 66.87% respectively in comparison with the general method of fixed expected impedance parameters, which verifies the feasibility and effectiveness of the proposed method.

     

/

返回文章
返回