Hybrid least-square adaptive bacterial foraging strategy for harmonic estimation

被引:48
|
作者
Mishra, S [1 ]
机构
[1] Indian Inst Technol Delhi, Dept Elect Engn, New Delhi 110016, India
关键词
D O I
10.1049/ip-gtd:20049016
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Harmonic estimation for a signal distorted with additive noise has been an area of interest for researchers in many disciplines of science and engineering. A new algorithm is presented, based on the foraging behaviour of E. coli bacteria in our intestine to estimate the harmonic components present in power systems voltage/current waveforms. The basic foraging strategy is made adaptive, depending on the operating condition, to make the convergence faster. The harmonic estimation is linear in amplitude and nonlinear in phase. As the proposed algorithm does not rely on Newton-like gradient-descent methods, it is used for phase estimation whereas the linear least-square scheme estimates the amplitude, thereby presenting the hybrid method. The improvement in percentage error as well as the processing time compared to the conventional genetic algorithm method is demonstrated. The percentage error in this new algorithm is less than 7% at 0 dB signal-to-noise ratio for Gaussian noise. The performance is quite acceptable even in the presence of decaying DC component as well as changes in amplitude and phase angle of harmonic components.
引用
收藏
页码:379 / 389
页数:11
相关论文
共 50 条
  • [21] Fast global motion estimation using iterative least-square estimation technique
    Sorwar, G
    Murshed, M
    Dooley, L
    ICICS-PCM 2003, VOLS 1-3, PROCEEDINGS, 2003, : 282 - 286
  • [22] ITERATIVE LEAST-SQUARE ESTIMATION FOR STRUCTURAL NONLINEARITY AND EXTERNAL LOADINGS IDENTIFICATION
    He, Jia
    Xu, Bin
    INNOVATION & SUSTAINABILITY OF STRUCTURES, VOLS 1 AND 2, 2011, : 449 - 454
  • [23] BINOCULAR ESTIMATION OF MOTION: A LEAST-SQUARE SOLUTION USING NORMAL FLOWS
    Hui, Tak-Wai
    Chung, Ronald
    2013 20TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP 2013), 2013, : 3830 - 3834
  • [24] Adaptive least-square deconvolution and its relation to minimum entropy deconvolution
    Li, XP
    JOURNAL OF SEISMIC EXPLORATION, 1997, 6 (01): : 59 - 76
  • [25] Adaptive order tracking technique using recursive least-square algorithm
    Bai, MSR
    Jeng, J
    Chen, CY
    JOURNAL OF VIBRATION AND ACOUSTICS-TRANSACTIONS OF THE ASME, 2002, 124 (04): : 502 - 511
  • [26] Least-square estimation for regression on random designs for absolutely regular observations
    Viennet, G
    STATISTICS & PROBABILITY LETTERS, 1999, 43 (01) : 13 - 23
  • [27] Estimation and inference of combining quantile and least-square regressions with missing data
    Tang, Linjun
    Zheng, Shengchao
    Zhou, Zhangong
    JOURNAL OF THE KOREAN STATISTICAL SOCIETY, 2018, 47 (01) : 77 - 89
  • [28] Application of least-square estimation in white-light scanning interferometry
    Ma, S.
    Quan, C.
    Zhu, R.
    Tay, C. J.
    Chen, L.
    Gao, Z.
    OPTICS AND LASERS IN ENGINEERING, 2011, 49 (07) : 1012 - 1018
  • [29] LEAST-SQUARE ESTIMATION OF PLASMA PARAMETERS FROM EXPERIMENTAL-DATA
    WANG, PKC
    BULLETIN OF THE AMERICAN PHYSICAL SOCIETY, 1976, 21 (09): : 1078 - 1078
  • [30] Linear least-square estimation algorithms involving correlated signal and noise
    Fernández-Alcalá, RM
    Navarro-Moreno, J
    Ruiz-Molina, JC
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2005, 53 (11) : 4227 - 4235