| 基于改进遗传算法的模糊RBF神经网络控制器设计 |
| |
| 引用本文： | 董玲娇,冯冬青. 基于改进遗传算法的模糊RBF神经网络控制器设计[J]. 计算技术与自动化, 2005, 24(4): 13-15 |
| |
| 作者姓名： | 董玲娇 冯冬青 |
| |
| 作者单位： | 温州职业技术学院电气电子工程系,浙江,温州,325035;郑州大学信息与控制研究所,河南,郑州,450002 |
| |
| 基金项目： | 河南省自然科学基金资助项目（0311011300） |
| |
| 摘 要： | 提出一种改进的优良模式自学习模糊遗传算法，并用来优化设计模糊RBF神经网络控制器。改进的算法主要基于模糊编码、优良模式自学习算子、保留遗传算法和最优串重组。仿真结果表明，改进的遗传算法可实现模糊RBF网络结构和参数的快速、全局寻优，优化后的控制器具有很强的自适应性和鲁棒性。
|
| 关 键 词： | 遗传算法 RBF神经网络 寻优 自适应 |
| 文章编号： | 1003-6199（2005）04-0013-03 |
| 收稿时间： | 2004-09-13 |
| 修稿时间： | 2004-09-13 |
Design of the Fuzzy RBF Neural Network Controller Based on Improved Genetic Algorithm |
| |
| DONG Ling-jiao,FENG Dong-qing. Design of the Fuzzy RBF Neural Network Controller Based on Improved Genetic Algorithm[J]. Computing Technology and Automation, 2005, 24(4): 13-15 |
| |
| Authors: | DONG Ling-jiao FENG Dong-qing |
| |
| Affiliation: | 1. School of Electric and Electronic Engineering, Wenzhou Vocational and Technical College, Wenzhou 325035, China; 2. Institue of Information and Control, Zhengzhou University, Zhengzhou 450002,China |
| |
| Abstract: | This paper presents an excellent schemas self- learning genetic algorithm, which is based on fuzzy coding, self- learning operator of optimal schemas, reserved genetic algorithm and the recombination of the optimal individual, And use it to design neuro- fuzzy RBF network controller. The results of simulation have shown that the modified genetic algorithm can find the global optimum structure and parameters of the network at a high speed and the controller based on improved genetic algorithm is self- adjusted and robust. |
| |
| Keywords: | genetic algorithm RBF neural network optimum self- adjusted |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
