期刊文献+

基于自适应模糊神经网络的水轮机特性辨识研究 被引量:7

Research on identification of hydraulic turbine model based on adapting fuzzy neural networks
下载PDF
导出
摘要 利用自适应模糊神经网络(ANFIS)较强的非线性逼近能力,建立了辨识模型,对水轮机非线性特性进行了辨识.训练算法采用最小二乘和梯度下降结合的算法来训练参数,模型能很好地辨识水轮机特性,并有一定的透明性,为研究智能水轮发电机控制策略提供了有效的建模方法. The identifying model of hydraulic turbine based on ANFIS neural networks are established by using the strong approaching ability of ANFIS network. In the design, parameters are trained according to minimization principle and steepest descent method. The designed model can well distinguish the characteristics of hydraulic turbine and is transparent to express the relation between input and output. Thus, the identifying model can lay the good foundation for the study on the intelligent control strategies for hydraulic turbine governor.
机构地区 华中科技大学
出处 《武汉大学学报(工学版)》 CAS CSCD 北大核心 2006年第2期24-27,共4页 Engineering Journal of Wuhan University
关键词 水轮机 ANFIS 径向基函数 模型辨识 hydraulic turbine ANFIS radial basis function model identification
  • 相关文献

参考文献4

  • 1Jiang Chang,Zhihuai Xiao,Shuqing Wang.Neural network predict control for the hydro turbine generator set[A].The Second International Conference on Machine Learning and Cybernetics(ICMLC2003)[C].2003.2-5.
  • 2Luciano Boquete,Rafael Barea,Ricardo Garcia.Identification and control of a wheelchair using recur-rent neural networks[J].Engineering Applications of Artificial Intelligence,1999,12(1):443-452.
  • 3Narendra K S.Identification and Control for Dynamic Systems using Neural Networks.IEEE,TransNN,1990,1(3):4-273.
  • 4Barry GommJ,DingLiYu.Selecting radial basis function network centers with recursive orthogonal least squares training[J].IEEE Transon Neural Networks,2000,11(2):306-314.

同被引文献51

引证文献7

二级引证文献27

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部