Adaptive Control of Active Power Filter Using RBF Neural Network

被引：0
|
作者：
Fei, Juntao [1 ]
Wang, Zhe [1 ]
机构：
[1] Hohai Univ, Coll Comp & Informat, Jiangsu Key Lab Power Transmiss & Distribut Equip, Changzhou 213022, Jiangsu, Peoples R China
来源：
2013 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION (ICMA) | 2013年
关键词：
Adaptive neural network; radial basis function; active power filter; NONLINEAR CONTROL; COMPENSATION; STRATEGY; DESIGN;
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：
An adaptive radial basis function (RBF) neural network control system for three-phase active power filter (APF) is proposed to eliminate the harmonics. Compensation current is generated to track command current so as to eliminate the harmonic current of non-linear load and improve the quality of power system. The asymptotical stability of the APF system can be guaranteed with the proposed adaptive neural network strategy. The parameters of neural network can be adaptively updated to achieve the desired tracking task. The simulation results demonstrate the good performance such as small current tracking error, reduced total harmonic distortion (THD), improved accuracy and strong robustness in the presence of parameters variation and nonlinear load. It is shown that adaptive RBF neural network control system for three-phase APF has better control effect than hysteresis control.
引用
收藏
页码：767 / 772
页数：6
相关论文
共 50 条
  • [41] Nonsingular Terminal Sliding Mode Control for Active Power Filter Using Recurrent Neural Network
    Wang, Huan
    Fei, Juntao
    IEEE ACCESS, 2018, 6 : 67819 - 67829
  • [42] Active power filter with a neural network controller
    Tong, Mei
    Tong, Jie
    Jiang, Jingping
    Diangong Jishu Xuebao/Transactions of China Electrotechnical Society, 2000, 15 (01): : 57 - 60
  • [43] Active power filter with a neural network controller
    2000, China Machine Press, China (15):
  • [44] Active disturbance rejection control with adaptive RBF neural network for a permanent magnet spherical motor
    Guo, Xiwen
    Tan, Ao
    Wang, Qunjing
    Li, Guoli
    Sun, Yuming
    Yang, Qiyong
    ISA TRANSACTIONS, 2025, 156 : 678 - 688
  • [45] Performance investigation of the shunt active power filter using neural network
    Suresh, Dhanavath
    Singh, S. P.
    2014 IEEE STUDENTS' CONFERENCE ON ELECTRICAL, ELECTRONICS AND COMPUTER SCIENCE (SCEECS), 2014,
  • [46] Adaptive Neural Network for a Stabilizing Shunt Active Power Filter in Distorted Weak Grids
    Asadi, Yousef
    Eskandari, Mohsen
    Mansouri, Milad
    Chaharmahali, Sajjad
    Moradi, Mohammad H.
    Tahriri, Mohammad Sajjad
    APPLIED SCIENCES-BASEL, 2022, 12 (16):
  • [47] An advanced active power filter with adaptive neural network based harmonic detection scheme
    Rukonuzzaman, M
    Nakaoka, M
    PESC 2001: 32ND ANNUAL POWER ELECTRONICS SPECIALISTS CONFERENCE, VOLS 1-4, CONFERENCE PROCEEDINGS, 2001, : 1602 - 1607
  • [48] RBF neural network robust adaptive control of quadrotor aircraft
    Ma Z.
    Bai H.
    Chen H.
    Wang J.
    Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics, 2024, 50 (05): : 1620 - 1628
  • [49] Adaptive PID control based on RBF neural network identification
    Zhang, MG
    Wang, XG
    Liu, MQ
    ICTAI 2005: 17TH IEEE INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, PROCEEDINGS, 2005, : 681 - 683
  • [50] RBF-neural network adaptive control of mobile manipulator
    Qian, Yang
    Wu, Xiongjun
    Wu, Shengtong
    Han, Fei
    2018 37TH CHINESE CONTROL CONFERENCE (CCC), 2018, : 5639 - 5646
12345