DocumentCode
2675996
Title
Elman dynamic neural network control for direct-drive feed system in advanced CNC machine tools
Author
Zuo, Jian-Min ; Pan, Chao ; Wang, Mu-Ian ; Su, Wei
Author_Institution
Sch. of Mech. Eng., Jiangsu Univ., Zhenjiang, China
Volume
2
fYear
2010
fDate
24-26 Aug. 2010
Firstpage
307
Lastpage
310
Abstract
Permanent Magnet Linear Synchronous Motors (PMLSM) are gaining increasing interest as direct-drive actuator for CNC machine tools. However, the servo control system of PMLSM is multi-variable, non-linear and strong-coupled and sensitizes to various force disturbances. For high speed and high precision to CNC machine tools, Elman dynamic Neural Network(NN) is introduced and the compound controller of Proportional(P) controller and Elman NN is proposed based on on-line training. Elman NN is trained by P controller at the beginning of control process. Then, speed loop of PMLSM servo system is controlled by Elman NN. The work process of proposed compound controller is exposed and dynamic characteristic of Elman NN is proved. The simulation results show that the proposed control scheme not only has strong robustness to uncertainties of the linear servo system, but also has good tracking precision and disturbance rejection abilities.
Keywords
computerised numerical control; linear synchronous motors; motor drives; neurocontrollers; permanent magnet motors; proportional control; robust control; servomechanisms; CNC machine tool; Elman dynamic neural network; PMLSM; compound controller; direct-drive actuator; multivariable system; nonlinear system; permanent magnet linear synchronous motor; proportional controller; servo control system; strong-coupled system; Adaptation model; Artificial neural networks; Robots; Robustness; CNC machine tools; Elman neural network; permanent magnet linear synchronous motors;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on
Conference_Location
Changchun
Print_ISBN
978-1-4244-7957-3
Type
conf
DOI
10.1109/CMCE.2010.5609807
Filename
5609807
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