基于模糊神经网络的发电机励磁控制器的研究  

STUDY ON THE GENERATOR EXCITATION CONTROLLER BASED ON FUZZY NEURAL NETWORK

作　　者：姜惠兰[1] 魏强[1] 唐晓骏[2] 

机构地区：[1]天津大学电气与自动化工程学院,天津市南开区300072 [2]中国电力科学研究院,北京市海淀区100085

出　　处：《电网技术》2005年第1期50-55,共6页Power System Technology

基　　金：天津大学留学回国人员基金资助项目(200447)。

摘　　要：在分析发电机励磁控制系统的基础上将模糊控制理论和神经网络技术有机结合,提出了基于模糊神经网络(Fuzzy Neural Network,FNN)的智能型励磁控制策略,构造了具有双FNN模型结构的励磁控制器。所构建的FNN励磁控制系统不仅保留了模糊控制的功能,而且具有体现励磁控制非线性特征的能力,能更精确地反映系统的动态变化过程,具有更强的鲁棒性和适应性。Based on the analysis of generator excitation control system and combining the fuzzy control theory with neural network technology, an intelligent excitation control strategy based on fuzzy neural network (FNN) is proposed, and an excitation controller with a structure of double FNN models is built. In this FNN excitation control system not only the functions of fuzzy control are retained, but also the ability to incarnate the non-linear feature of excitation control is provided, the dynamic changing process of the excitation system can be reflected more precisely, therefore, the proposed system possesses better robustness and adaptability.

关 键 词：发电机 励磁控制器 励磁控制系统 模糊神经网络 模糊控制理论 智能型 神经网络技术 FNN 鲁棒性 模型结构 

分 类 号：TM31[电气工程—电机] TP273[自动化与计算机技术—检测技术与自动化装置]