ELECTROMAGNETISM, OPTICS, ACOUSTICS, HEAT TRANSFER, CLASSICAL MECHANICS, AND FLUID DYNAMICS |
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Frequency detection of self-adaption control based on chaotic theory |
Xu Yan-Chun (徐艳春), Qu Xiao-Dong (瞿晓东), Li Zhen-Xing (李振兴) |
College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China |
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Abstract Low-order Duffing and high-order Rössler chaotic oscillator are connected together and new self-adaption frequency detection method is presented. The frequency difference control between unknown signal and the periodic driving force is realized in this paper and the self-adaption is obtained. Thus, the detection precision and speed are promoted. The limitation that there are too many chaotic oscillators in Duffing system is broken. Meanwhile the disadvantage that the detection speed is lower in Rössler chaotic control is overcome. The self-adaption choice of frequency difference control is realized using the Duffing and Rössler different chaotic oscillators to obtain unknown signal frequency. The simulation results show that the presented method is feasible and effective.
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Received: 05 July 2014
Revised: 28 September 2014
Accepted manuscript online:
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PACS:
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43.60.Qv
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(Signal processing instrumentation, integrated systems, smart transducers, devices and architectures, displays and interfaces for Acoustic systems)
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05.45.-a
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(Nonlinear dynamics and chaos)
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05.45.Jn
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(High-dimensional chaos)
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Fund: Project supported by the Talent Scientific Research Foundation of China Three Gorges University (Grant No. KJ2013B079). |
Corresponding Authors:
Qu Xiao-Dong
E-mail: quxd@hlju.edu.cn
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Cite this article:
Xu Yan-Chun (徐艳春), Qu Xiao-Dong (瞿晓东), Li Zhen-Xing (李振兴) Frequency detection of self-adaption control based on chaotic theory 2015 Chin. Phys. B 24 034301
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[1] |
Wu H, How Z and Xin H 2010 Chaos 20 043140
|
[2] |
Zhang Y, Lu S and Wang Y H 2009 Chin. Phys. Lett. 26 090501
|
[3] |
Bao B C, Liu Z and Xu J P 2010 Chin. Phys. B 19 030510
|
[4] |
Zhou J C and Song H J 2012 J. Korean Phys. Soc. 61 1303
|
[5] |
Qin Z Y and Lu Q S 2007 Chin. Phys. Lett. 24 886
|
[6] |
Rosenblum M and Pikovsky A 2007 Phys. Rev. Lett. 98 064101
|
[7] |
Shaw L B, Schwartz I B, Rogers E A and Roy R 2006 Chaos 16 015111
|
[8] |
Sun X J and Lu Q S 2009 Chin. Phys. Lett. 26 060507
|
[9] |
Yu H T, Wang J, Deng B and Wei X L 2013 Chin. Phys. B 22 018701
|
[10] |
Horio Y, Aihara K and Yamarmoto O 2003 IEEE Trans. Neural Netw. 5 1399
|
[11] |
Yuan L, Shen J Q, Xiao F and Chen M L 2013 Acta Phys. Sin. 62 030501 (in Chinese)
|
[12] |
Chen L, Peng H J and Wang D S 2008 Acta Phy. Sin. 57 3337 (in Chinese)
|
[13] |
Tang Z J, Ren F and Peng T 2014 Acta Phy. Sin. 63 050505 (in Chinese)
|
[14] |
Wu J S, Jiao L C and Chen G R 2011 Chin. Phys. B 20 060503
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