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基于思维进化算法的模糊自寻优控制 被引量：1

The Research of Mind Evolutionary Algorithm-based Fuzzy control with Self-optimizing
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摘要 在一维调整因子法的基础上,提出了二维调整因子的概念,并用思维进化算法对模糊控制系统的量化因子、比例因子、二维调整因子进行自寻优。仿真实验结果表明了该方法优于一维调整因子法。 In this paper,based on one-dimensional adjusting factor, two-dimensional adjusting factor was proposed ,and MEA was adapted to optimize quantified factor, proportional factor and two-dimensional adjusting factor of self-optimizing fuzzy control. In comparison with one-dimensional adjusting factor, a simulation was carried and showed the superiority of two-dimensional adjusting factor.
作者 韩晓霞 谢克明
机构地区 太原理工大学信息工程学院
出处 《太原理工大学学报》 CAS 2004年第5期523-525,共3页 Journal of Taiyuan University of Technology
基金 国家自然科学基金资助项目(60374029) 山西省留学回国人员基金资助项目(200027)
关键词 思维进化算法 模糊控制 二维调整因子 自寻优 mind evolutionary algorithm fuzzy control two-dimensional adjusting factor self-optimizing
分类号 TP181 [自动化与计算机技术—控制理论与控制工程]
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参考文献4

  • 1李玉惠,李勃.用梯度误差角修正模糊控制量[J].控制理论与应用,2000,17(5):771-773. 被引量：1
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二级参考文献3

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同被引文献10

  • 1杨易曼.基于极限学习的系统辨识方法及应用研究[D].长沙:湖南大学,2013:19-22.
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太原理工大学学报
2004年 第5期

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