Research of High Speed Spindle Control Method Based on Neural Network

Jie Meng; Ze Lun Li; Zhong Liang Lv; Min Liu

doi:10.4028/www.scientific.net/AMR.834-836.1177

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 834-836Research of High Speed Spindle Control Method...

Research of High Speed Spindle Control Method Based on Neural Network

Abstract:

High speed spindle is a multivariable and strong coupling complex system. In order to improve its dynamic response characteristics and control effectively, based on vector control, the high speed spindle needs to be decoupling first. Then neural network theory and BP algorithm are adopted to form a speed controller to adjust the rotational speed. In this controller, gradient searching technique is applied and the proportional and integral parameters are used as weight of neural network which is employed to adjust the corresponding control parameters. Therefore, a new model of high speed spindle is set up and simulated. The result of simulation indicates that the way combine the decoupling method and the speed controller based on neural network can track the rotational speed more accurate and promote the robustness of high speed spindle.

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Periodical:

Advanced Materials Research (Volumes 834-836)

Pages:

1177-1181

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.834-836.1177

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Online since:

October 2013

Authors:

Jie Meng*, Ze Lun Li, Zhong Liang Lv, Min Liu

Keywords:

BP Algorithm, Decoupling Method, High Speed Spindle, Neural Network (NN), Speed Controller

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References

[1] Jie Meng: Advanced Materials Research Vol. 291-294 (2011), p.3078.

Google Scholar

[2] Huimin Kang, Huiqiang Li, Jie Meng: Journal of Hunan University of Science & Technology (Natural Science Edition), Vol. 27, No. 4(2012), p.18. (In Chinese).

Google Scholar

[3] Jie Meng, Zhenzhen Lei, Zelun Li: Applied Mechanics and Materials, Vol. 288 (2013), p.202.

Google Scholar

[4] ChengHung Tsai: 2006 IEEE Conference on Systems, Man, and Cybernetics, (2006), p.5297.

Google Scholar

[5] F. F. M. El-Sousy: IEEE ICIT '04, Vol. 1 (2004), p.418.

Google Scholar

[6] Jelonkiewicz, J., Przyby, A: ICAISC 2008, Vol. 5097(2008), p.71.

Google Scholar

[7] Cozma, A., Pitica, D: OPTIM, (2008), p.161.

Google Scholar