计算机科学
执行机构
气动人工肌肉
极限(数学)
控制器(灌溉)
控制理论(社会学)
软机器人
模拟
控制工程
控制(管理)
人工肌肉
人工智能
工程类
数学分析
农学
生物
数学
作者
Guizhou Cao,Bing Chu,Benyan Huo,Yanhong Liu
标识
DOI:10.1142/s0219843621500043
摘要
Inspired by nature, soft-bodied pneumatic network actuators (PNAs) composed of compliant materials have been successfully applied in the fields of industry and daily life because of large-amplitude motion and long life span. However, compliant materials simultaneously limit the output force, challenge the dynamic modeling and impede corresponding control. In this paper, we investigate the design, modeling and control of an enhanced PNA. First, an enhanced structure is proposed to improve the output force of PNAs with features of simplification of fabrication, lightweight and compliant material retentivity. Second, a dynamic model of the enhanced PNA is constructed based on the Euler–Lagrange (EL) method. Finally, an adaptive robust controller is addressed for PNAs in presence of system uncertainties without knowledge of its bounds in prior. Experiment results show that the output force of the enhanced PNA is four times greater than the actuator without enhanced structures, which affords to theoretical estimation. Moreover, the proposed controller is utilized and compared with previous works in humanoid finger experiments to illustrate the effectiveness.
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