基于RBF神经网络的核电站高压加热器水位优化控制  

Control of HP-Heater′s Water Level and Optimization of PID Parameters Based on RBF Neural Network

作　　者：钱虹[1] 辛浩[1] 张杨[1] 

机构地区：[1]上海电力学院电力与自动化工程学院,上海200090

出　　处：《上海电力学院学报》2011年第5期503-506,共4页Journal of Shanghai University of Electric Power

摘　　要：以方家山/福清核电工程的高压加热器为研究对象,介绍了高压加热器水位控制的建模与参数调节.先用试凑法对PI控制调节器的调节参数进行预整定,再通过RBF神经网络整定算法进行优化.最后,使用整定参数对加热器进行3种情况的扰动测试,结果表明控制器在不同工况下的控制性均能满足控制要求.Using Fangjiashan nuclear power of the high-pressure heater project in Fuqing as research object, a method to rectify the parameter regulation of high-pressure heater water control regulator is described first;then, the advanced RBF neural network is used to optimize it. Finally, the setting parameter is adopted to have disturbation test on the three conditions of heater, testifying the control characteristics of the controller in different conditions and all the requirements are met.

关 键 词：高压加热器 水位控制 RBF神经网络 核电站 

分 类 号：TU822[建筑科学] TP273[自动化与计算机技术—检测技术与自动化装置]