Study on Integral-Separate PID Improved Predictive Control for Electro-Hydraulic Control System of Strip Steel CPC

Article Preview

Abstract:

As electro-hydraulic control system of strip steel CPC has some special characteristics, such as strong nonlinear, changes in structural parameters, serious time-delay and the very difficultly of establishing accurate mathematical model, the integral-separate PID improved predictive control algorithm was proposed on the basis of the new mathematical model. Firstly, the integral-separate PID algorithm was used to make system asymptotic stability and reduce overshoot of system. Secondly, the predictive control algorithm was proposed, error feedback correction model was improved, and predictive control signal was optimized with rolling method. Finally, the system was simulated and analyzed in noise and pulse disturbance. The simulation results show that this algorithm can effectively improved abilities of anti-noise and anti-load disturbance, increases robustness and tracking capability of strip steel CPC system; furthermore, it can improved speed of system response and decrease time-delay and overshoot of system. Therefore, this algorithm can well meet the need of electro-hydraulic control system for strip steel CPC system.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

250-256

Citation:

Online since:

December 2011

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Xin Jingtai, Zhang Qiang, Zhen Yongfu, et al: Equipment Manufactring Technology. Vol. 1(2008), p.6 (in Chinese).

Google Scholar

[2] Li Yongtang, Lei BuFang, Gao Yuzhuo: Modeling and Simulation for Hydraulic System (Metallurgical Industry Press, China 2003) (in Chinese).

Google Scholar

[3] Ge Baoming, Lin Fei, Li GuoGuo: Advanced Control Theory and its Applications.(China Machine Press, China 2007) (in Chinese).

Google Scholar

[4] Zafiriou, Evanghelos, Morari, Manfred: International Journal of Control, Vol. 42(1985), p.855 (in English).

Google Scholar

[5] Ye Xiaohua, Cen Yuwan, Zhao Han, et al: China Mechanical Engineering, Vol. 22(2011), p.23 (in Chinese).

Google Scholar

[6] Mahadevan R., Doyle III F.J. "Efficient optimization approaches to nonlinear model predictive control", International Journal of Robust and Nonlinear Control, Vol. 13, n. 3-4, 309-329, March/April 2003(in English).

DOI: 10.1002/rnc.820

Google Scholar