Intelligent adaptive control of machining process based on hybrid recurrent neural network

被引：0

作者：

Lai, Xing-Yu ^{[1
]}

Yan, Chun-Yan ^{[1
]}

Ye, Bang-Yan ^{[2
]}

Li, Wei-Guang ^{[2
]}

机构：

[1] Guangdong Inst Sci & Technol, Dept Mechatron Engn, Guangzhou 510640, Peoples R China

[2] South China Univ Technol, Coll Mech Engn, Guangzhou 510640, Peoples R China

来源：

PROCEEDINGS OF 2007 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2007年

关键词：

intelligent; adaptive control; machining process; hybrid recurrent neural network;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Aiming at the feasibility of intelligent adaptive control for a machining process, a new network architecture, called a hybrid recurrent neural network (HRNN) is first presented based on the diagonal recurrent neural network (DRNN). Considering the uncertain information in the machining process, a generalized entropy square error (GESE) criterion is then proposed. The learning algorithm of the HRNN and the mathematic model of the machine tool for experiments are also explained. Finally, the HRNN is applied to the constant force control of the machining process. Simulated results verify the effectiveness of the proposed control schemes. And the experimental results also confirm the applicability of the described controller in practice.

引用

页码：676 / +

页数：3

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