Proceedings of the 2018 3rd International Conference on Control, Automation and Artificial Intelligence (CAAI 2018)

A Bi-normalized Frequency Estimation Algorithm

Authors
Zhaobi Chu, Yan Wang, Rui Zhang
Corresponding Author
Zhaobi Chu
Available Online August 2018.
DOI
https://doi.org/10.2991/caai-18.2018.30How to use a DOI?
Keywords
frequency estimation; adaptive internal model; bi-normalization; robustness
Abstract

This paper presents a bi-normalized frequency estimation algorithm which contains a two-dimensional state estimation equation and a one-dimensional frequency update rule coupled with it. The robustness of the algorithm is that the frequency estimation convergence is no longer subject to the actual value of the amplitude and frequency of the estimated signal. The asymptotic convergence of frequency estimation is demonstrated by Lyapunov stability theory, perturbation method, integral manifold and Mathieu equation, and the relationship between adaptive internal model algorithm and the proposed bi-normalization algorithm is analyzed. Simulation results verify the effectiveness of the proposed algorithm.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 3rd International Conference on Control, Automation and Artificial Intelligence (CAAI 2018)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
August 2018
ISBN
978-94-6252-595-5
ISSN
2589-4919
DOI
https://doi.org/10.2991/caai-18.2018.30How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Zhaobi Chu
AU  - Yan Wang
AU  - Rui Zhang
PY  - 2018/08
DA  - 2018/08
TI  - A Bi-normalized Frequency Estimation Algorithm
BT  - Proceedings of the 2018 3rd International Conference on Control, Automation and Artificial Intelligence (CAAI 2018)
PB  - Atlantis Press
SP  - 126
EP  - 129
SN  - 2589-4919
UR  - https://doi.org/10.2991/caai-18.2018.30
DO  - https://doi.org/10.2991/caai-18.2018.30
ID  - Chu2018/08
ER  -