DocumentCode
3255367
Title
Neuron net control and its application in precision feed mechanism of machine tools driven by PZT
Author
Zhaoquan, Lu ; Daojiong, Chen ; Huifang, Kong ; Wang Guornei ; Fen, Xie ; Jingwei, Wang
Author_Institution
Dept. of Electr. Eng., Anhui Inst. of Technol., Hefei, China
fYear
1996
fDate
2-6 Dec 1996
Firstpage
80
Lastpage
82
Abstract
In this paper a novel monolayer neural net model and learning algorithm are proposed to control a precision feed mechanism driven by piezoelectric ceramics (PZT) of machine tools. Experiment shows that the neural net control enables the cutter to trace the teaching signals rapidly and accurately, although the PZT cutter feed mechanism has characteristics of nonlinearity and hysteresis
Keywords
cutting; lead compounds; learning systems; machine tools; neurocontrollers; perceptrons; piezoceramics; tracking; cutter; feed mechanism; hysteresis; learning algorithm; machine tools; neural net control; nonlinear systems; nonlinearity; piezoelectric ceramics; precision; Ceramics; Control system synthesis; Education; Feeds; Hysteresis; Integrated circuit modeling; Machine learning; Machine tools; Mathematical model; Neurons;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Technology, 1996. (ICIT '96), Proceedings of The IEEE International Conference on
Conference_Location
Shanghai
Print_ISBN
0-7803-3104-4
Type
conf
DOI
10.1109/ICIT.1996.601545
Filename
601545
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