基于对角回归神经网络的饱和式蒸汽发生器水位控制  

DRNN Based Control for Water Level of Saturated Steam Generator

作　　者：王颖民[1] 瞿小龙[2] 崔震华 

机构地区：[1]西南交通大学电气工程学院,成都610031 [2]中国核动力研究设计院,成都610041 [3]Atlantic Nuclear Services Ltd Canada

出　　处：《核动力工程》2007年第3期90-93,124,共5页Nuclear Power Engineering

摘　　要：神经网络具有较强的自学习和自适应能力,本文设计了基于对角回归神经网络(DRNN)的控制系统,选择合适的学习率,实现饱和式蒸汽发生器水位变化率的快速稳定辨识和自适应控制。仿真结果表明,蒸汽发生器水位的控制效果良好。The neural network has strong self-learning and self-adapting abilities. Presented in this paper is a diagonal recurrent neural network-based control system that is applied to quick and stable identification and self-adaptive level control of the saturated steam generator. The simulation results demonstrate that the developed control system is with good control performances.

关 键 词：对角回归神经网络 蒸汽发生器 水位控制 

分 类 号：TL361[核科学技术—核技术及应用]