使用动态量化器对麦基本气动执行器进行长度控制

IF 1.5 Q3 INSTRUMENTS & INSTRUMENTATION
Yasuhiro Sugimoto, Keisuke Naniwa, Daisuke Nakanishi, Koichi Osuka
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引用次数: 0

摘要

麦基本气动执行器(MPA)是一种软执行器,通过压缩空气膨胀橡胶管来施加张力。虽然电动气动调节器可以控制气压,但大多体积庞大、价格昂贵。本研究利用动态量化器来控制 MPA,用一个只能打开和关闭阀门的小型电磁阀来代替电动气动调节器。动态量化器是将连续信号转换为离散信号的量化器之一。我们之前的研究证实,使用动态量化器可以实现等距条件下 MPA 的张力控制。然而,通常需要控制 MPA 的长度以及 MPA 的张力。本研究利用一个小型电磁阀实现了动态量化器对 MPA 长度的控制。数值模拟和实验测试验证了所提方法的有效性。数值模拟和实验测试的结果证实,使用动态量化器可以控制 MPA 的长度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Length control of a McKibben pneumatic actuator using a dynamic quantizer
McKibben pneumatic actuators (MPAs) are soft actuators that exert tension by applying compressed air to expand a rubber tube. Although electro-pneumatic regulators can control air pressure, most are large and expensive. This study utilizes a dynamic quantizer to control the MPA with a small solenoid valve that can only open and close the valve instead of an electro-pneumatic regulator. A dynamic quantizer is one of the quantizers that converts continuous signals to discrete signals. Our previous study confirmed that tension control of MPA under isometric conditions could be realized using a dynamic quantizer. However, it is often necessary to control the length of the MPA as well as the tension of the MPA. This study implements a dynamic quantizer to control the length of the MPA with a small solenoid valve. Numerical simulations and experimental tests verify the effectiveness of the proposed method. The results of the numerical simulations and experimental tests confirmed that the length of the MPA can be controlled using the dynamic quantizer.
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来源期刊
ROBOMECH Journal
ROBOMECH Journal Mathematics-Control and Optimization
CiteScore
3.20
自引率
7.10%
发文量
21
审稿时长
13 weeks
期刊介绍: ROBOMECH Journal focuses on advanced technologies and practical applications in the field of Robotics and Mechatronics. This field is driven by the steadily growing research, development and consumer demand for robots and systems. Advanced robots have been working in medical and hazardous environments, such as space and the deep sea as well as in the manufacturing environment. The scope of the journal includes but is not limited to: 1. Modeling and design 2. System integration 3. Actuators and sensors 4. Intelligent control 5. Artificial intelligence 6. Machine learning 7. Robotics 8. Manufacturing 9. Motion control 10. Vibration and noise control 11. Micro/nano devices and optoelectronics systems 12. Automotive systems 13. Applications for extreme and/or hazardous environments 14. Other applications
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