Tracking Voltage Flicker Envelope Using Cumalant-based RLS Algorithm with Variable Forgetting Factor

被引:1
|
作者
Chen, Xiaodong [1 ]
Ma, Qian [1 ]
Qu, Zuyi [1 ]
Liu, Miao [1 ]
Jin, Xiaoming [1 ]
Li, Dalu [1 ]
Chen, Han [2 ]
机构
[1] Liaoning Elect Power Co Ltd, Liaoning, Peoples R China
[2] Shenyang Elect Supply Co Liaoning, Shenyang, Peoples R China
关键词
Gaussian noise; higher-order Cumulant; RLS algorithm; variable forgetting factor; voltage flicker envelope; HILBERT TRANSFORM;
D O I
10.4028/www.scientific.net/AMM.281.568
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The cumalant-based RLS algorithm with variable forgetting factor is introduced in this paper as effective approach for tracking the voltage flicker envelope. The improved RLS algorithm uses the fourth-order cumulant-based mean-squared-error (MSE) criterion in place of correlation-based MSE criterion, in order to suppress the Gaussian noise. For tracking nonstationary voltage flicker waveform, variable forgetting factor (VFF) can be applied to adjust the tracking performance and convergence performance of algorithm. Two cases of flicker with constant amplitude and frequency and varying amplitude and frequency are used to verify the performance of algorithm.
引用
收藏
页码:568 / +
页数:2
相关论文
共 50 条
  • [41] Low-Complexity Variable Forgetting Factor Constant Modulus RLS-based Algorithm for Blind Adaptive Beamforming
    Qin, Boya
    Cai, Yunlong
    Champagne, Benoit
    Zhao, Minjian
    Yousefi, Siamak
    2013 ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS, 2013, : 171 - 175
  • [42] A low-complexity variable forgetting factor constant modulus RLS algorithm for blind adaptive beamforming
    Qin, Boya
    Cai, Yunlong
    Champagne, Benoit
    de Lamare, Rodrigo C.
    Zhao, Minjian
    SIGNAL PROCESSING, 2014, 105 : 277 - 282
  • [43] A Robust Variable Forgetting Factor QS-decomposition Algorithm for Subspace Tracking
    Lin, J. Q.
    Chan, S. C.
    2018 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2018,
  • [44] A QR Decomposition Based RLS Algorithm with Forgetting Factor for Adaptation of AR EEG Features
    Iqbal, Hira
    Aqil, Muhammad
    2016 INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES (ICET), 2016,
  • [45] Diversity-based diffusion robust RLS using adaptive forgetting factor
    Sadigh, Alireza Naeimi
    Yazdi, Hadi Sadoghi
    Harati, Ahad
    SIGNAL PROCESSING, 2021, 182
  • [46] RLS Algorithm with Variable Forgetting Factor for Decision Feedback Equalizer over Time-Variant Fading Channels
    Zhuang W.
    Wireless Personal Communications, 1998, 8 (1) : 15 - 29
  • [47] Prognosis of Bearing Degradation Using Gradient Variable Forgetting Factor RLS Combined With Time Series Model
    Lu, Yanfei
    Li, Qing
    Pan, Zhipeng
    Liang, Steven Y.
    IEEE ACCESS, 2018, 6 : 10986 - 10995
  • [48] Run-to-Run Fault Prediction for Semiconductor Manufacturing Process Based On Variable Forgetting Factor RLS
    Liu, Shujie
    Zheng, Ying
    Luo, Ming
    CHINA SEMICONDUCTOR TECHNOLOGY INTERNATIONAL CONFERENCE 2012 (CSTIC 2012), 2012, 44 (01): : 1175 - 1184
  • [49] Application of Recursive Least Square (RLS) Algorithm with Variable Forgetting Factor for Frequency Components Estimation in a Generic Input Signal
    Beza, Mebtu
    Bongiorno, Massimo
    2012 IEEE ENERGY CONVERSION CONGRESS AND EXPOSITION (ECCE), 2012, : 2164 - 2171
  • [50] Adaptive Turbo Equalization with Sparse Homotopy DCD-RLS Algorithm with Variable Forgetting Factor for Underwater Acoustic Communication
    Zhang Youwen
    Liu Lu
    Sun Dajun
    2016 IEEE/OES CHINA OCEAN ACOUSTICS SYMPOSIUM (COA), 2016,