Abstract
Double self-adaptive fuzzy PID algorithm-based control strategy was proposed to construct quasi-cascade control system to control the speed of the acid-pickling process of titanium plates and strips. It is very useful in overcoming non-linear dynamic behavior, uncertain and time-varying parameters, un-modeled dynamics, and couples between the automatic turbulence control (ATC) and the automatic acid temperature control (AATC) with varying parameters during the operation process. The quasi-cascade control system of inner and outer loop self-adaptive fuzzy PID controller was built, which could effectively control the pickling speed of plates and strips. The simulated results and real application indicate that the plates and strips acid pickling speed control system has good performances of adaptively tracking the parameter variations and anti-disturbances, which ensures the match of acid pickling temperature and turbulence of flowing with acid pickling speed, improving the surface quality of plates and strips acid pickling, and energy efficiency.
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YAO Zhong-mao, YU Jie-dong, HUANG Fu-ya-zhi. Choice and application of pickling and rolling line for cold-rolled strip steel [J]. Henan Metallurgy, 2007, 15(2): 11–14. (in Chinese)
MAGDALENA R R. A review on methods of regeneration of spent pickling solutions from steel processing [J]. Journal of Hazardous Materials, 2010, 177(1): 57–69.
DING Zhi-yu, JIN Zhi-yong. Analysis and optimization of turbulence pickling technology for cold rolling [J]. Angang Technology, 2008, 351(3): 42–45. (in Chinese)
AMAL K E S, NABIL A M, NEVEEN A M, SAWSAN H. Interventional environmental study and health survey in metal pickling process [J]. Toxicology Letters, 2006, 164: 1–324.
WU Yan-juan, LIU Bi-ying, LIU Chun-qing. The process and main equipment characteristics of continuous pickling line [J]. Metallurgical Equipment, 2005, 152(4): 58–61. (in Chinese)
KLADNIG W F. New development of acid regeneration in steel pickling plants [J]. Journal of Iron and Steel Research, International, 2008, 15(4): 1–6.
MAO Hang-biao. Based on information of control of automatic control system for pickling line [J]. Coal Technology, 2009, 28(9): 162–163. (in Chinese)
WACHIRA D, PIYANUCH T, AMORNCHAI A, PAISAN K, MOHAMED A H. Neural network inverse model-based controller for the control of a steel pickling process [J]. Computers & Chemical Engineering, 2005, 29(10): 2110–2119.
PAISAN K, PIYANUCH T, HUSSAIN M A, WACHIRA D. Neural network based model predictive control for a steel pickling process [J]. Journal of Process Control, 2009, 19(4): 579–590.
YE Chun-jie, PAN Hong-liang. Numerical simulation and parameter analysis of turbulent pickling tank by fluent [J]. Journal of Nanjing University of Technology: Natural Science Edition, 2009, 31(5): 34–41. (in Chinese)
ZHOU Zhi-hui, YANG Jie. Characteristic of push-pull pickling line and its technical development [J]. Wisco Technology, 2010, 48(2): 49–52. (in Chinese)
CHEN Long-gong, HUANG Wei. Cold-rolled steel sheet pickling process and equipment [M]. Beijing: The Metallurgical Industry Press, 2005: 77–83. (in Chinese)
ZHU J, KUZNETSOV A V, SANDEEP K P. Mathematical modeling of continuous flow microwave heating of liquids (effects of dielectric properties and design parameters) [J]. International Journal of Thermal Sciences, 2007, 46(4): 328–341.
WANG Shao-lin. The application of microwave heating technology -Dry and sterilization [M]. Beijing: Machinery Industry Press, 2003: 1–5. (in Chinese)
TONG Shao-cheng, HE Xiang-lei, LI Yong-ming. Adaptive fuzzy backstepping robust control for uncertain nonlinear systems based on small-gain approach [J]. Fuzzy Sets and Systems, 2010, 161(6): 771–796.
SOYGUDER S, KARAKOSE M, Hasan A. Design and simulation of self-tuning PID-type fuzzy adaptive control for an expert HVAC system [J]. Expert Systems with Application, 2009, 36(3): 4566–4573.
KARAM M E, JIAO Zong-xia, ZHANG Hua-qing. PID controller optimization by GA and its performances on the electro-hydraulic servo control system [J]. Chinese Journal of Aeronautics, 2008, 21(4): 378–384.
RONG Hui-gui, ZHENG Hui, LI Zheng-qiang, XIA Yu-xiang. Tuning of fuzzy PID controller for Smith predictor [J]. Journal of Central South University of Technology, 2010, 17(3): 566–571.
CHENG Yi, ZHUANG Cheng, AN Xie-nan. A general fuzzy logic controller and its application [J]. Acta Automatica Sinica, 1992, 18(6): 647–654. (in Chinese)
PRECUP R E, HELLENDOORN H. A survey on industrial applications of fuzzy control [J]. Computers in Industry, 2011, 62(3): 213–226.
PHAN P A, GALE T J. Direct adaptive fuzzy control with a self-structuring algorithm [J]. Fuzzy Sets and Systems, 2008, 159(8): 871–899.
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Foundation item: Project(51090385) supported by the National Natural Science Foundation of China; Project(2001IB001) supported by Yunnan Provincial Science and Technology Fund, China
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Yang, B., Peng, Jh., Guo, Sh. et al. Acid-pickling plates and strips speed control system by microwave heating based on self-adaptive fuzzy PID algorithm. J. Cent. South Univ. 19, 2179–2186 (2012). https://doi.org/10.1007/s11771-012-1262-4
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DOI: https://doi.org/10.1007/s11771-012-1262-4