Radial basis function neural network vibration control of a flexible planar parallel manipulator based on acceleration feedback

被引：4

作者：

Yu, Long-huan ^{[1
]}

Qiu, Zhi-cheng ^{[1
]}

Zhang, Xian-min ^{[1
]}

机构：

[1] South China Univ Technol, Guangdong Key Lab Precis Equipment & Mfg Technol, Guangzhou, Guangdong, Peoples R China

来源：

JOURNAL OF VIBRATION AND CONTROL | 2022年 / 28卷 / 3-4期

基金：

中国国家自然科学基金;

关键词：

Flexible planar 3-RRR parallel manipulator; self-excited vibration control; acceleration feedback; radial basis function neural network; experiments; SELF-EXCITED VIBRATION; 3-RRR; ACTUATION;

D O I：

10.1177/1077546320977400

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

The self-excited vibration of flexible planar 3-RRR parallel manipulators is converted from the residual vibration after high-speed motion and is a resonance of the strongly coupled and nonlinear electromechanical system. This makes the active vibration control quite a challenging task. In this study, we attempt to adopt the radial basis function neural network control algorithm based on acceleration feedback for suppressing the self-excited vibration and guarantee its position accuracy. The stability of the controlled system is proved by the Lyapunov concept. Self-excited vibration control experiments are conducted near the singular region. Experimental results demonstrate the effectiveness of our adopted controller.

引用

页码：351 / 363

页数：13

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