Regulation of PID Controller Parameters Based on Ant Colony Optimization Algorithm in Bending Control System

Yu Zhen Yu; Xin Yi Ren; Chun Yan Deng; Jing Jing Yu; Shu Zhen Li; Jun Jie Shi

doi:10.4028/www.scientific.net/AMM.128-129.205

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 128-129Regulation of PID Controller Parameters Based on...

Regulation of PID Controller Parameters Based on Ant Colony Optimization Algorithm in Bending Control System

Abstract:

The bending-roll control system has characteristics of time-varying, time-delay, nonlinearity and serious external disturbance, so it is hard to establish precise math model that be applied to control. In view of the problems above, ant colony algorithm is used to tuning parameters of PID controller and concrete step of PID parameters tuning based on ant colony algorithm is given. The simulation results indicate that the method not only improves control performance and dynamic quality, but also has strong self-adapting ability and robustness. It achieved a very good control effect when used in bending control system that proved the correctness and effectiveness of the control method.

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Periodical:

Applied Mechanics and Materials (Volumes 128-129)

Pages:

205-210

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.128-129.205

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Online since:

October 2011

Authors:

Yu Zhen Yu, Xin Yi Ren, Chun Yan Deng, Jing Jing Yu, Shu Zhen Li, Jun Jie Shi

Keywords:

Ant Colony Algorithm (ACA), Hydraulic Bending System, Parameters Regulation, PID Controller

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References

[1] Chen li, Li jiangeng, Fuzzy Neural Network Model Reference Adaptive Control Method for the Hydraulic Bending Roll in the Control System of UC Rolling Mill, Fluid Transmission and Control, 2004(3): 4-5. (in Chinese).

Google Scholar

[2] Wang yiqun, Liu yu, Fuzzy controller based on adaptive genetic algorithm for a electro-hydraulic bending control system, Chinese Journal of Construction Machinery, 2006, 4(2): 159-163. (in Chinese).

Google Scholar

[3] Wang yiqun, Sun fu, Application of PID Neural Network in Electro-hydraulic Bending Control System, Machine Tool and Hydraulics, 2008, 36(3): 83-85. (in Chinese).

Google Scholar

[4] Bonabeau E. Dorigo, M. Theraulaz G, Inspiration for Optimization from Social Insect Behaviou, NATURE, 2000, 406(6): 39-42.

DOI: 10.1038/35017500

Google Scholar

[5] Christian Blum, Ant Colony Optimization Introduction and Recent Trends, Physics of Life Reviews, 2005(2): 353.

DOI: 10.1016/j.plrev.2005.10.001

Google Scholar

[6] Huseyin Atakan Varol, Zafer Bingul, A New PID Tuning Technique Using Ant Algorithm, Proceeding of the 2004 American Control Conference, 2004(3): 2145.

DOI: 10.23919/acc.2004.1383780

Google Scholar