Fuzzy Neural Model for Flatness Pattern Recognition

钢铁研究学报(英文版), 2008, 15(6): 33-38.

^1, , ^2, , ^3, , ^4,

1.School of Mechanical Engineering,Yanshan University,Qinhuangdao 066004,Hebei,China

2.School of Mechanical Engineering,Yanshan University,Qinhuangdao 066004,Hebei,China

3.School of Mechanical Engineering,Yanshan University,Qinhuangdao 066004,Hebei,China

4.School of Mechanical Engineering,Yanshan University,Qinhuangdao 066004,Hebei,China

基金项目: 国家自然科学基金(50575186) 河北省自然科学基金(E2006001038)

Fuzzy Neural Model for Flatness Pattern Recognition

JIA Chun-yu ^1, , SHAN Xiu-ying ^2, , LIU Hong-min ^3, , NIU Zhao-ping ^4,

1.School of Mechanical Engineering,Yanshan University,Qinhuangdao 066004,Hebei,China

2.School of Mechanical Engineering,Yanshan University,Qinhuangdao 066004,Hebei,China

3.School of Mechanical Engineering,Yanshan University,Qinhuangdao 066004,Hebei,China

4.School of Mechanical Engineering,Yanshan University,Qinhuangdao 066004,Hebei,China

Keywords： flatness

For the problems occurring in a least square method model,a fuzzy model,and a neural network model for flatness pattern recognition,a fuzzy neural network model for flatness pattern recognition with only three-input and three-output signals was proposed with Legendre orthodoxy polynomial as basic pattern,based on fuzzy logic expert experiential knowledge and genetic-BP hybrid optimization algorithm.The model not only had definite physical meanings in its inner nodes,but also had strong self-adaptability,anti-interference ability,high recognition precision,and high velocity,thereby meeting the demand of high-precision flatness control for cold strip mill and providing a convenient,practical,and novel method for flatness pattern recognition.

参考文献

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Fuzzy Neural Model for Flatness Pattern Recognition

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