基于线性二次调节优化技术的下肢康复机器人自适应导纳控制*

Renyu Yang, Jie Zhou, R. Song
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引用次数: 2

摘要

柔顺、自然、安全的人机物理交互对康复机器人具有现实意义。在我国最新研制的下肢康复机器人(LLRR)中,设计了一种基于线性二次调节(LQR)优化技术的自适应导纳控制,可根据人机交互系统的变阻抗特性同步调节参数。首先,设计了计算转矩PD控制,保证了轨迹跟踪的准确性和稳定性;其次,设计了一个观测器来估计协作任务中人机交互扭矩(HRIT)。最后,采用LQR优化技术对导纳模型参数进行优化,使跟踪误差和人力最小化。仿真研究结果表明,观测器能够正确估计HRIT,期望轨迹随相互作用力矩平滑正确地变形。
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Adaptive Admittance Control Based on Linear Quadratic Regulation Optimization Technique for a Lower Limb Rehabilitation Robot*
Compliant, natural and safe physical human-robot interaction is of practical significance for rehabilitation robots. In our recently developed lower limb rehabilitation robot (LLRR), an adaptive admittance control based on linear quadratic regulation (LQR) optimization technique was designed to regulate parameters synchronously with the variable impedance property of human-robot interactive system. Firstly, a computed torque PD control was designed to guarantee the accuracy and stability of trajectory tracking. Secondly, an observer was designed to estimate human-robot interaction torque (HRIT) during cooperative task. Finally, a LQR optimization technique was employed to optimize admittance model parameters and minimize tracking errors and human efforts. Simulation studies were conducted on the LLRR and the results show that the HRIT can be estimated by the observer correctly and the desired trajectory was deformed smoothly and rightly with the interaction torque.
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