Facilitating On-Line Harmonic Estimation Based on Robust Adaptive RBFNN

被引：0
|
作者：
Almaita, Eyad K. [1 ]
Al Shwawreh, Jumana [1 ]
机构：
[1] TafilaTechn Univ, Dept Elect Power & Mechatron Engn, Tafila, Jordan
来源：
2019 SIXTH INTERNATIONAL CONFERENCE ON SOCIAL NETWORKS ANALYSIS, MANAGEMENT AND SECURITY (SNAMS) | 2019年
关键词：
Energy efficiency; Power quality; Radial basis function; neural networks; adaptive; harmonic;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, An adaptiveRadial Basis Function Neural Networks (RBFNN) algorithm is used to estimate the fundamental and harmonic components of nonlinear load current. The learning rates for adaptive RBFNN are further investigated to minimize the total error and to minimize the error in each of the fundamental and harmonics components. The performance of the adaptive RBFNN is evaluated based on the difference between the original signal and the constructed signal (the summation between fundamental and harmonic components). The methodology used in this paper facilitates the development and design of signal processing and control systems. This is done by training the system and obtaining the initial parameters for the RBFNN based on simulation. After that, the adaptive RBFNN can be in the real system with these initial parameters.
引用
收藏
页码：484 / 488
页数：5
相关论文
共 50 条
  • [21] On-line robust control based on an external loop
    Wu, WT
    Hwang, ZP
    [J]. CHEMICAL ENGINEERING COMMUNICATIONS, 1995, 137 : 101 - 110
  • [22] On-Line Monitoring and Fault Diagnos of Box Transformer Substation Based on VPRS-RBFNN
    Xu, Erbao
    Li, Yan
    Yang, Mingshun
    Xiao, Renhao
    Lin, Hairui
    Gao, Xinqin
    [J]. TEHNICKI VJESNIK-TECHNICAL GAZETTE, 2020, 27 (06): : 1965 - 1973
  • [23] Adaptive linear learning for on-line harmonic identification: An overview with study cases
    Wira, Patrice
    Thien Minh Nguyen
    [J]. 2013 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2013,
  • [24] Nonlinear on-line Estimation and Adaptive Control of a Wastewater Treatment Bioprocess
    Roman, M.
    Selisteanu, D.
    [J]. ELEKTRONIKA IR ELEKTROTECHNIKA, 2012, 117 (01) : 23 - 28
  • [25] Adaptive Control of a Civil Aircraft Through On-Line Parameter Estimation
    Ferreres, G.
    Hardier, G.
    Seren, C.
    [J]. 2016 3RD CONFERENCE ON CONTROL AND FAULT-TOLERANT SYSTEMS (SYSTOL), 2016, : 798 - 804
  • [26] An incremental adaptive network for on-line supervised learning and probability estimation
    Lim, CP
    Harrison, RF
    [J]. NEURAL NETWORKS, 1997, 10 (05) : 925 - 939
  • [27] Robust Adaptive Back-stepping Control Design Based on RBFNN for Morphing Aircraft
    Qiao, Fuxiang
    Zhang, Weiguo
    Li, Guangwen
    Shi, Jingping
    Qu, Xiaobo
    Che, Jun
    Zhou, Haijun
    [J]. 2018 IEEE CSAA GUIDANCE, NAVIGATION AND CONTROL CONFERENCE (CGNCC), 2018,
  • [28] Adaptive On-line Registration Algorithm Based on GLR
    Lian, Feng
    Han, Chongzhao
    Shi, Yong
    [J]. 2008 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-8, 2008, : 2220 - 2226
  • [29] Robust on-line fault detection diagnosis for HVAC components based on nonlinear state estimation techniques
    Bonvini, Marco
    Sohn, Michael D.
    Granderson, Jessica
    Wetter, Michael
    Piette, Mary Ann
    [J]. APPLIED ENERGY, 2014, 124 : 156 - 166
  • [30] Cooperative robust adaptive control of multiple trains based on RBFNN position output constraints
    Yang, Junxia
    Zhang, Youpeng
    Jin, Yuxiang
    [J]. EXPERT SYSTEMS, 2024, 41 (06)
12345