| 引用本文: | 张 斌, 王景成, 张健民.基于模糊系统和遗传算法的加热炉动态模型(英文)[J].控制理论与应用,2003,20(2):293~296.[点击复制] |
| ZHANG Bin, WANG Jing-cheng, ZHANG Jian-min.Dynamic model of reheating furnace based on fuzzy system and genetic algorithm[J].Control Theory and Technology,2003,20(2):293~296.[点击复制] |
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| 基于模糊系统和遗传算法的加热炉动态模型(英文) |
| Dynamic model of reheating furnace based on fuzzy system and genetic algorithm |
| 摘要点击 1859 全文点击 1166 投稿时间：2000-03-21 修订日期：2002-01-09 |
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| DOI编号 |
| 2003,20(2):293-296 |
| 中文关键词 模糊系统 遗传算法 结构辨识 加热炉模型 |
| 英文关键词 fuzzy system genetic algorithm structure identification reheating furnace model |
| 基金项目 |
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| 中文摘要 |
| 介绍了一种由采样数据确定模糊模型结构的方法. 方法中变量上的隶属函数个数不断增加并通过性能评价来确定是否保留这些操作, 该过程重复直至变量上的隶属函数个数确定下来. 该方法被用于加热炉的建模并由遗传算法来调节其中的参数. 仿真结果证明了这种方法的有效性. |
| 英文摘要 |
| A simple method is introduced to determine the structure of the fuzzy model. In this process, the membership function on each variable is increased separately in each iteration and performance is evaluated to decide whether to continue this operation. This procedure continues till the numbers of membership functions on all the variables are fixed. The method is used to a reheating furnace and parameters thereof are tuned by adaptive genetic algorithm. Simulations show the effectiveness of the constructed system. |