| 基于遗传算法的过热度模糊控制因子优化研究 |
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| 引用本文： | 伞兵,吴钢.基于遗传算法的过热度模糊控制因子优化研究[J].低温与超导,2010,38(6). |
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| 作者姓名： | 伞兵 吴钢 |
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| 作者单位： | 海军工程大学船舶与动力学院,武汉,430033 |
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| 摘 要： | 模糊控制器的量化因子和比例因子对蒸发器过热度的调节品质影响极大。针对传统"试凑法"选择量化因子和比例因子时主观因素强且难以实现全局最优的缺点,采用遗传算法对两类模糊因子进行优化。仿真结果表明:优化后的模糊控制器动态、静态性能均优于传统模糊控制器。
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| 关 键 词： | 遗传算法 模糊控制器 量化因子 比例因子 蒸发器过热度 |
Optimization research on superheat fuzzy control factors based on genetic algorithms |
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| San Bing,Wu Gang.Optimization research on superheat fuzzy control factors based on genetic algorithms[J].Cryogenics and Superconductivity,2010,38(6). |
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| Authors: | San Bing Wu Gang |
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| Institution: | San Bing,Wu Gang(College of Naval Architecture and Power,Naval University of Engineering,Wuhan 430033,China) |
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| Abstract: | Both the scaling factor and the numerical factor of fuzzy controller had great influence on evaporator superheat's adjusting quality.Because of the subjectivity and the difficulty in reaching global optimum when using the conventional trial-and-error method to select the scaling factor and the numerical factor,the Genetic Algorithm was applied to optimize these two kinds of fuzzy factors.The simulation result shows that both the dynamic and the static performance of the optimized fuzzy controller are more e... |
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| Keywords: | Genetic algorithm Fuzzy controller Scaling factor Numerical factor Evaporator superheat |
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