变刚度机器人关节的模糊自适应控制器研究

郭怀超 ,  哈乐 ,  刘佳龙 ,  崔浩东 ,  张明 ,  孙兴伟

科学技术与工程 ›› 2024, Vol. 24 ›› Issue (28) :12220-12226

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科学技术与工程 ›› 2024, Vol. 24 ›› Issue (28) :12220-12226 DOI: 10.12404/j.issn.1671-1815.2401126
自动化技术、计算机技术

变刚度机器人关节的模糊自适应控制器研究

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Fuzzy Adaptive Controller for Variable Stiffness Robot Joint

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摘要

为了增强人机交互的安全性和环境适应能力,提出了一种新颖的变刚度机器人关节样机。采用永磁体和空心电磁线圈构成变刚度机构,可通过调整系统的磁通量实现关节刚度的快速改变。基于分子电流法和虚位移法成功构建了变刚度关节的刚度模型。随后,开发了变刚度关节位置与刚度协调控制器以及模糊自适应控制器。实验结果表明:在不断增加关节刚度的情况下,关节位置和轨迹跟踪的精度得到提高,而随着运动频率的增加,精度呈下降趋势。模糊自适应控制器在控制该变刚度关节位置阶跃和轨迹跟踪性能方面要优于传统控制器,具有更好的跟踪精度与更快的响应速度。

Abstract

To enhance the safety and adaptability of human-machine interaction, a novel variable stiffness robot joint prototype was proposed. This prototype employed permanent magnets and hollow electromagnetic coils to form the variable stiffness mechanism, enabling rapid adjustment of joint stiffness by manipulating the system's magnetic flux. The stiffness model of the variable stiffness joint was successfully established based on molecular current method and virtual displacement method. Subsequently, controllers for coordinating joint position and stiffness, as well as a fuzzy adaptive controller, were developed. Experimental results indicate that increasing joint stiffness leads to improved accuracy in joint position and trajectory tracking, albeit with a decreasing trend in precision as motion frequency rises. The fuzzy adaptive controller outperforms traditional controllers in controlling the step response and trajectory tracking performance of the variable stiffness joint, exhibiting superior tracking accuracy and faster response speed.

关键词

永磁体 / 磁通量 / 变刚度 / 模糊自适应 / 跟踪精度

Key words

permanent magnet / magnetic flux / variable stiffness / fuzzy adaptive control / tracking accuracy

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郭怀超, 哈乐, 刘佳龙, 崔浩东, 张明, 孙兴伟. 变刚度机器人关节的模糊自适应控制器研究[J]. 科学技术与工程, 2024, 24(28): 12220-12226 DOI:10.12404/j.issn.1671-1815.2401126
GUO Huai-chao, HA Le, LIU Jia-long, CUI Hao-dong, ZHANG Ming, SUN Xing-wei. Fuzzy Adaptive Controller for Variable Stiffness Robot Joint[J]. Science Technology and Engineering, 2024, 24(28): 12220-12226 DOI:10.12404/j.issn.1671-1815.2401126

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基金资助

辽宁省科技厅面上项目(2022-MS-271)

国家自然科学基金(52005344)

国家重点研发计划(2020YFC2006701)

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