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Robust Variable Stiffness Control of McKibben Type Pneumatic Artificial Muscle Arm by using Multiple Model Error Compensators

机译:使用多模型误差补偿器使用多模型误差器型气动人工肌肉鲁棒变量刚度控制

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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.
机译:当人类与机器人共存时,机器人需要安全的柔性运动。软致电器将是制造安全机器人的关键。麦克宾型气动人工肌肉(PAM)是代表性的软执行器,并且已在许多领域中广泛使用。但是,软件和精确控制之间存在权衡。本研究旨在对PAM臂的准确变形刚度控制。为了控制PAM臂,角度,压力和刚度控制器使用模型误差补偿器(MEC)设计,以增加鲁棒性。根据灵活性和精度要求选择性地,实现了可变刚度控制系统。最后,通过使用一个环形PAM臂进行实验来评估所提出的方法的有效性。

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