| 基于自适应模糊聚类的神经网络软测量建模方法 |
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| 引用本文： | 王锡淮,李少远,席裕庚.基于自适应模糊聚类的神经网络软测量建模方法[J].控制与决策,2004,19(8):951-953. |
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| 作者姓名： | 王锡淮 李少远 席裕庚 |
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| 作者单位： | 1. 上海海事大学,电气自动化系,上海,200135;上海交通大学,自动化研究所,上海,200030
2. 上海交通大学,自动化研究所,上海,200030 |
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| 基金项目： | 国家自然科学基金资助项目(69934020，60074004)，上海市教委科技发展基金资助项目(03IK09). |
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| 摘 要： | 提出一种基于模糊聚类的神经网络软测量建模方法．该方法采用数据分组训练、自动确定模糊分类数、在线测量时分类中心自适应修正，降低了计算量，提高了建模精度．将该算法用于步进式加热炉钢坯温度预报的仿真结果表明，它能够解决钢坯温度难以在线测量的问题。
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| 关 键 词： | 软测量 神经网络 模糊聚类 加热炉 钢坯温度 |
| 文章编号： | 1001-0920(2004)08-0951-03 |
| 修稿时间： | 2003年5月1日 |
Neural network soft sensor modeling method based on adaptive fuzzy clustering |
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| WANG Xi-huai.Neural network soft sensor modeling method based on adaptive fuzzy clustering[J].Control and Decision,2004,19(8):951-953. |
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| Authors: | WANG Xi-huai |
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| Affiliation: | WANG Xi-huai~ |
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| Abstract: | A neural network soft sensor modeling method based on fuzzy clustering is presented. The training data set is separated into several clusters with different centers, the number of fuzzy cluster is decided automatically, and the clustering centers are modified using an adaptive fuzzy clustering algorithm in the online stage. This method can reduce the calculation remarkably and has good prediction accuracy. The proposed method has been applied to the slab temperature estimation in a practical walking beam reheating furnace. Simulation results show that the method can deal with the measuring problem of the slab temperature in heating process online. |
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| Keywords: | soft sensor neural network fuzzy clustering reheating furnace slab temperature |
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