| 基于人工智能的自适应板形控制 |
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| 引用本文： | 贾春玉.基于人工智能的自适应板形控制[J].钢铁研究学报,2001,13(4):58-61. |
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| 作者姓名： | 贾春玉 |
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| 作者单位： | 燕山大学机械工程学院 |
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| 摘 要： | 针对板带材轧制过程是一个复杂的非线性过程及传统板形控制模型的固有缺陷，为了提高冷轧带钢的板形质量和成材率，提出一种基于神经网络模糊推理的自适应板形控制（AI－AFC）方案，并将其引入森吉米尔20辊轧机的板形控制系统。离线仿真结果表明：该系统具有良好的控制性能，可提高板形控制质量。
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| 关 键 词： | 人工智能 神经网络 模糊推理 森吉米尔轧机 板形控制 |
| 文章编号： | 1001-0963(2001)04-0058-04 |
| 修稿时间： | 2000年4月5日 |
Self-Adaptive Flat Control Based on Artificial In telligence |
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| JIA Chun,yu.Self-Adaptive Flat Control Based on Artificial In telligence[J].Journal of Iron and Steel Research,2001,13(4):58-61. |
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| Authors: | JIA Chun yu |
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| Abstract: | A scheme of self adaptive flat control based on neural network fuzzy inference (AI AFC) was put forward for quality and yield improvement of cold rolled strip, with the consideration of rolling process as a complicated non linear process and the intrinsic defects in traditional flat control models. The simulation result evinced that the AI AFC system has good enough performance when the model is used in the flat control system on Sendzimir 20 high mill. |
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| Keywords: | artificial intelligence neural network fuzzy inference Sendzimir 20 high mill flat control |
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