| 基于改进遗传算法的模糊神经网络控制 |
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| 引用本文： | 宋清昆,姜雷,郝敏.基于改进遗传算法的模糊神经网络控制[J].电机与控制学报,2005,9(6):617-620. |
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| 作者姓名： | 宋清昆 姜雷 郝敏 |
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| 作者单位： | 哈尔滨理工大学,自动化学院,黑龙江,哈尔滨,150080;哈尔滨理工大学,自动化学院,黑龙江,哈尔滨,150080;哈尔滨理工大学,自动化学院,黑龙江,哈尔滨,150080 |
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| 摘 要： | 针对常规遗传算法的缺陷，提出了一种依据新的种群“早熟”程度评价指标和自适应调整算法参数的遗传算法，并以单级倒立摆为被控对象，采用基于改进遗传算法的RBF模糊神经网络控制器进行了仿真研究。仿真结果表明，改进的遗传算法是有效的，新型模糊神经网络控制器的控制效果优于FLC和LQR控制。
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| 关 键 词： | 遗传算法 RBF 自适应 |
| 文章编号： | 1007-449X（2005）06-0617-04 |
| 收稿时间： | 2004-04-20 |
| 修稿时间： | 2005-10-09 |
Research of the fuzzy neural network control based on the improved genetic algorithms |
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| SONG Qing-kun,JIANG Lei,HAO Min.Research of the fuzzy neural network control based on the improved genetic algorithms[J].Electric Machines and Control,2005,9(6):617-620. |
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| Authors: | SONG Qing-kun JIANG Lei HAO Min |
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| Abstract: | In view of the shortcomings of the normal genetic algorithms, an improved self - adaptive GA based on a new evolution index of the premature degree of population is proposed. The fuzzy RBF neural network controller, which is used in controlling the single inverted pendulum, is base on the proved GA.The simulation shows the improved GA is feasible and the control effect of this controller is superior to that of FLC and LQR. |
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| Keywords: | RBF |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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