基于模糊神经网络的发电机励磁控制器的研究

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(FuzzyNeural 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.

STUDY ON THE GENERATOR EXCITATION CONTROLLER BASED ON FUZZY NEURAL NETWORK

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.