基于多模型误差补偿器的McKibben型气动人工肌肉臂鲁棒变刚度控制

Yuto Yamamoto, N. Matsunaga, Hiroshi Okajima
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引用次数: 4

摘要

当人与机器人共存时,对机器人的安全柔性运动提出了要求。软执行器将是制造安全机器人的关键。McKibben型气动人造肌肉(PAM)是具有代表性的软执行器,在许多领域得到了广泛的应用。然而,在软驱动和精确控制之间存在权衡。本课题旨在对PAM机械臂进行精确的变刚度控制。在PAM臂的控制中,采用模型误差补偿器(MEC)设计了角度、压力和刚度控制器,提高了控制器的鲁棒性。根据柔性和精度要求,有选择地实现变刚度控制系统。最后,通过单连杆PAM臂的实验验证了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust variable stiffness control of McKibben type pneumatic artificial muscle arm by using multiple model error compensators
When human co-exists with robots, the secure flexible motion will be required for the robots. The soft-actuator will be a key to make a safe robot. McKibben type pneumatic artificial muscle (PAM) is representative soft actuator, and has been used widely in many fields. However, there is a trade-off between the soft actuation and the precise control. This study aims to an accurate variableness stiffness control of PAM arm. To control the PAM arm, the angle, pressure and stiffness controllers are designed using Model Error Compensator (MEC) to increase robustness. According to flexibility and accuracy requirement selectively, the variable stiffness control system is implemented. Finally, the effectiveness of proposed method is evaluated by experiment using one link PAM arm.
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