下肢助力外骨骼机器人自适应阻抗控制研究

Learning-Based Adaptive Impedance Control for a Human-Powered Augmentation Lower Exoskeleton

当前用于人体运动增强的下肢助力外骨骼系统获得越来越多的关注。获取高精度跟随控制是下肢助力外骨骼机器人研制的主要挑战。针对当前基于位置的控制算法需要复杂的外骨骼动力学模型的问题,该文提出了基于增强学习的变参数阻抗控制算法。首先介绍了HUALEX助力外骨骼系统并对HUALEX建立简单动力学模型。基于此,提出一种基于增强学习的自适应阻抗控制算法,验证了阻抗参数对控制效果的影响,并通过仿真实验验证了该算法的有效性。

A learning-based adaptive impedance control algorithm for a human-powered augmentation lower exoskeleton （HUALEX） is presented. The HUALEX system architecture is introduced first, which is divided into three parts including the mechanical subsystems, the sensing subsystem and the control subsystem. By using impedance control method, the inverse dynamics model of HUALEX is established and the control effect of impedance parameters is studied. And then, a reinforcement learning-based adaptive impedance control algorithm, including the reinforcement learning, PI2 （policy improvement with path integrals） learning algorithm and adaptive impedance control, is proposed. The effectiveness of the algorithm is verified simulation experiment.