The Study of BP Neural Network PID Control Based on the Cutting Chatter Suppression System

Dao Kun Zhang; Rui Huo; Shu Ying Li; Xing Ke Cui; Cui Ping Liu

doi:10.4028/www.scientific.net/AMR.1030-1032.1574

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 1030-1032The Study of BP Neural Network PID Control Based...

The Study of BP Neural Network PID Control Based on the Cutting Chatter Suppression System

Abstract:

The intelligent control strategy of BP neural combined network with classical PID control is mainly studied and simulated. The advantages of the control strategy are discussed. Based on the simulated data, the BP neural network PID control has the stronger adaptive ability.

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Periodical:

Advanced Materials Research (Volumes 1030-1032)

Pages:

1574-1577

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1030-1032.1574

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Online since:

September 2014

Authors:

Dao Kun Zhang*, Rui Huo, Shu Ying Li, Xing Ke Cui, Cui Ping Liu

Keywords:

BP Neural Network (BPNN), Chatter, PID

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References

[1] Jessica M, Yellin, Shen I Y. A Self-sensing Active Constrained Layer Damping Treatmeat for An Euler-Bernoulli Beam[J]. Smart Materials and Structures, 1996. 5: 628-637.

DOI: 10.1088/0964-1726/5/5/011

Google Scholar

[2] Veni P, Wen Y K. Hybrid Vibration Control of MDOF hysteretic Structures with Neural Networks[C]. Proeedings of First World Conference of Structure Control, TA3, losAngeles: 1994, 53-62.

Google Scholar

[3] Xiaoning Chen. the research of active vibration control method Based on neural network[D]. Master degree theses of master of Harbin engineering university, (2004).

Google Scholar

[4] Jinhou Li. The research progress and prospect of neural network[J]. 2000, 17(4): 275-281.

Google Scholar

[5] Shaoming Li, Wei Zhao. The simulink simulation of BP neural network PID controller based on the S function [J]. (2008).

Google Scholar