摘要
使用线性自适应性网络神经元(ADALINE)结构分析谐波.基于网络神经元最小均方差算法在线快速地跟踪电力系统电压或电流信号的基波和谐波分量,可分别跟踪各次波的幅值和频率.同时基于李雅普诺夫函数(Lyapunov Function)动态改变神经元网络中的学习率,为系统提供一个更快捷、稳定的收敛速度即跟踪基波谐波的相关参数.
The research used the adaptive linear neural network (ADALINE) to estimate the harmonic components.With on-line tracking of the fundamental signal and the harmonics of the currents and voltages in the power system by using ADALINE, the amplitude and the frequency of the harmonics can be tracked.On the other hand, the adaptive variation of the learning parameters provides more stable and faster convergence for the system,i.e tracking the parameters of the fundamental and harmonics.
出处
《安徽工程大学学报》
CAS
2017年第2期43-46,共4页
Journal of Anhui Polytechnic University
基金
安徽工程大学校青年基金资助项目(2017YQ06)