华南理工大学学报(自然科学版) ›› 2021, Vol. 49 ›› Issue (6): 19-27.doi: 10.12141/j.issn.1000-565X.200498

所属专题: 2021年机械工程

• 机械工程 • 上一篇    下一篇

柔性穿戴式上肢康复机器人关节运动控制研究

翟宇毅 马新愿 陈冬冬 雷静桃   

  1. 上海大学 机电工程与自动化学院,上海 200444
  • 收稿日期:2020-08-20 修回日期:2020-12-29 出版日期:2021-06-25 发布日期:2021-06-01
  • 通信作者: 雷静桃(1970-),女,博士,教授,主要从事仿生机器人技术研究。 E-mail:jtlei2000@163.com
  • 作者简介:翟宇毅(1963-),女,博士,副教授,主要从事特种机器人技术研究。E-mail:yyzhai@shu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(51775323)

Research on Joint Motion Control of Soft Wearable Upper Limb Rehabilitation Robots

ZHAI Yuyi MA Xinyuan CHEN Dongdong LEI Jingtao   

  1. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
  • Received:2020-08-20 Revised:2020-12-29 Online:2021-06-25 Published:2021-06-01
  • Contact: 雷静桃(1970-),女,博士,教授,主要从事仿生机器人技术研究。 E-mail:jtlei2000@163.com
  • About author:翟宇毅(1963-),女,博士,副教授,主要从事特种机器人技术研究。E-mail:yyzhai@shu.edu.cn
  • Supported by:
    Supported by the National Natural Science Foundation of China(51775323)

摘要: 针对传统康复机器人重量重、穿戴不便、运动柔顺性差等不足,基于轻量化、柔顺性、易穿戴和人体工学等设计原则,设计了一种柔性穿戴式上肢康复机器人。采用弹性布作为机器人基体,气动人工肌肉驱动的类拮抗式关节,实现了肘关节屈/伸及旋前/旋后运动。基于气动人工肌肉的力学特性模型,采用拉格朗日法建立了康复机器人的动力学模型。针对气动人工肌肉驱动的柔性系统易抖振、响应滞后的控制难点,设计了基于RBF神经网络的PID控制器;针对PID控制器初始参数依靠经验取值的问题,设计了模糊PID控制器以确定PID控制器的最优初始参数;最后通过仿真和实验研究对RBF-PID控制器的性能进行了验证,并与传统PID控制器进行了对比。结果表明:RBF-PID控制器响应速度快,控制稳定性高,可实现该柔性康复机器人的稳定控制。

关键词: 穿戴式康复机器人, 柔顺性, 气动人工肌肉, RBF神经网络, RBF-PID控制器

Abstract: A soft wearable upper limb rehabilitation robot was designed based on the principles of light weight, flexibility, easy-wear and ergonomics to make up the shortcomings of traditional rehabilitation robot, such as heavy weight, difficult to wear and poor motion flexibility. The robot body was make of elastic cloth and the pneumatic artificial muscle(PAM)was used as the antagonistic driving joint of the actuator to realize the elbow flexion/extension and pronation/supination motion. Moreover, the dynamic model of the rehabilitation robot is established according to the mathematical model of the new PAM and Lagrange dynamic equation. Aiming at the control difficulties of the soft system driven by PAMs, such as easy chattering and delayed response, a PID controller based on RBF neural network was designed. Aiming at the problem that the initial parameters of PID controller depend on experience, the fuzzy PID controller was designed to determine the optimal initial parameters of PID controller. Finally, the performance of the RBF-PID controller was verified through simulation and experimental research, and was compared with the traditional PID controller. The results show that the RBF-PID controller has fast response speed and high control stability, and it can realize the stable control of the soft rehabilitation robot.

Key words: wearable rehabilitation robot, soft, pneumatic artificial muscle, RBF neural network, RBF-PID control

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