融入可控阻尼的康复机器人自适应交互控制

Adaptive Interactive Control of Rehabilitation Robot with Controllable Damping

针对外骨骼康复机器人的人机交互柔顺控制,以肩-肘二自由度上肢康复机器人为研究对象,提出一种融入可控阻尼的内外环嵌套式自适应阻抗控制方法,同步实现关节轨迹的超调量抑制和变强度训练。首先,通过磁流变阻尼器与关节电动机并联输出的结构模式,将电磁阻尼力矩引入康复机器人的动力学方程,进而设计关节轨迹跟踪器作为内环控制器,该控制器以关节角速度和角加速度作为输入,实时计算调整阻尼力矩的励磁电流值和关节力矩增益系数,实现超调量抑制。其次,利用Lyapunov函数设计自适应轨迹生成器作为外环控制器,该控制器以交互力、关节角速度及角加速度作为输入,实时计算并修正期望轨迹,通过调节对抗模型的刚度参数,实现对人机交互力的自适应和变强度训练。数值仿真实验结果表明,与未引入可控阻尼的控制方法相比,肩、肘关节的超调量下降率分别优于96.2%、97.5%,且只需调整刚度参数即能实现变强度训练,验证了所提方法的可行性与有效性。

In order to synchronously realize the overshoot suppression of joint trajectory and variable strength training in the human-computer interaction compliant control of exoskeleton rehabilitation robot,an internal and external loop nested adaptive impedance control method with controllable damping is proposed,in which a shoulder-elbow two-degree of freedom upper limb rehabilitation robot is adopted as the research object.Firstly,a joint trajectory tracker as an inner loop controller is designed,in which the electromagnetic damping torque is introduced into the dynamic equation of the rehabilitation robot through the structural mode output by the magnetorheological damper and the joint motor in parallel.It takes angular velocity and angular acceleration vectors of moving joints as inputs and calculates the excitation current value and the joint torque gain coefficient to adjust the damping moment to suppress the overshoot.Secondly,an adaptive trajectory generator as an outer loop controller is designed by utilizing Lyapunov functions,in which the human-computer interaction force,joint angular velocity and angular acceleration are employed as input to real-time computing and correction of the desired trajectory,and it by adjusting the fighting stiffness of the model parameters to realize the human-computer interaction force and adaptive strength training.Finally,numerical simulation experiments show that compared with the control method without controllable damping,the overshoot of shoulder joint and elbow joint under the proposed method are better than 96.2%and 97.5%respectively,and the variable strength training is realized only by adjusting the stiffness parameters,which verifies the feasibility and effectiveness of the proposed method.