Neural Network Approximation Based Multi-dimensional Active Control of Regenerative Chatter in Micro-milling

被引：1
|
作者：
Liu, Xiaoli [1 ]
Su, Chun-Yi [1 ,2 ]
Li, Zhijun [1 ]
机构：
[1] South China Univ Technol, Coll Automat Sci & Engn, Guangzhou 510641, Guangdong, Peoples R China
[2] Concordia Univ, Dept Mech & Ind Engn, Montreal, PQ H3B 1R6, Canada
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2016 | 2016年 / 9719卷
关键词：
Micro-milling; Regenerative chatter; Adaptive neural control; Lyapunov; Krasovskii functional; MACHINE; PREDICTION; SYSTEMS; STABILITY; DESIGN;
D O I：
10.1007/978-3-319-40663-3_29
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, an active control approach with the employments of two piezoelectric actuators, the Neural Networks (NNs) as approximators and the Lyapunov-Krasovskii functional which is used to deal with the time delayed tool vibrations is investigated for suppressing the 2-dof regenerative chatter in micro-milling. A dynamic model of micro-milling process and corresponding controlled system are established. Simulations are presented to validate the control performances of developed control approach.
引用
收藏
页码：250 / 259
页数：10
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