Research on Heavy Rail Pre-Bending Vehicle Control Technology Based on Fuzzy Neural Network

Zhi Jun Xu; Guo Fu Yin

doi:10.4028/www.scientific.net/AMR.201-203.2379

Paper Titles

Design and Realization of Remote Monitoring System for Automatic Forced Fitting Production Line
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Slider Position Servo Control of the Double Toggle Mechanical Press Directly Driven by Transverse Flux Machine
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Concise Robust Control for Ship Roll Motion Using Active Fins
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Design of GA-Based Control for Electrical Servo Drive
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Research on Heavy Rail Pre-Bending Vehicle Control Technology Based on Fuzzy Neural Network
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Self-Sencing Control Research on a Linear Compressor
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Research on the Control and Key Technology for Parallel Operation System of Mobile Generator
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Embedded Control Design for Insulin Pump
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Fuzzy ADRC Controller Design for PMSM Speed Regulation System
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 201-203Research on Heavy Rail Pre-Bending Vehicle Control...

Research on Heavy Rail Pre-Bending Vehicle Control Technology Based on Fuzzy Neural Network

Abstract:

The natural cooling after the rolling of the 100-meter-long rail tends to curve the rail from the bottom to the head. Based on the analysis of the rail pre-bending process, this thesis proposes the implementation plan of the pre-bending vehicle control system. The position loop uses fuzzy neural network regulator and the speed loop uses PB-based neural network PID regulator. Also the thesis gives the corresponding control algorithm. The control equipment uses Siemens advanced SIMATIC PCS7 process control system. Through experimental analysis, the dynamic tracking performance and the static accuracy of the system are guaranteed and the vehicle is accurately placed as expected.

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Periodical:

Advanced Materials Research (Volumes 201-203)

Pages:

2379-2384

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.201-203.2379

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Online since:

February 2011

Authors:

Zhi Jun Xu, Guo Fu Yin

Keywords:

Automatic Control, Fuzzy Neural Network (FNN), Heavy Rail, Pre-Bending

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References

[1] Shengli Song: Survey of Intelligent Control Technology, Defense Science and Technology Publishing House, Beijing (2008), in Chinese.

Google Scholar

[2] Hui Hu and Guorong Liu: Research on Fuzzy Neural Network Control and Its Learning Methods, Journal of Hunan Institute of Engineering, Vol. 3 (2006), in Chinese.

Google Scholar

[3] Haiyang Sun, Wenying Li and Jinhong Wei: Design of Intelligent Temperature Controller based on Neural Network PID , Mechanical Engineering & Automation, Vol. 2 (2005), in Chinese.

Google Scholar

[4] Di Liu and Jianhua Zhao: Self-adaptation PID Control Algorithm based on Model of BP Neural Network , Control Theory & Applications, Vol. 8 (2008), in Chinese.

Google Scholar

[5] Yikang Sun and Jing Wang: Basics of Metallurgical Process Automation, China Machine Press, Beijing (2006), in Chinese.

Google Scholar

[6] Cosmin D B, Jose S D C, Vasile P.: A novel fuzzy calassification solution for faullt diagnosis [J], Joural of Intelligent & Fuzzy System, 2004, 15.

Google Scholar

[7] Na Man Gyun, Park Kyung Ho: Senior monitoring using a fuzzy neural network with an automatic Structure, Ieee Transaction on Nuclear Science, 2003, 5.

DOI: 10.1109/tns.2003.809471

Google Scholar