Parameter Identification of Fractional-Order Discrete Chaotic Systems
Research on fractional-order discrete chaotic systems has grown in recent years, and chaos synchronization of such systems is a new topic. To address the deficiencies of the extant chaos synchronization methods for fractional-order discrete chaotic systems, we proposed an improved particle swarm opt...
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doaj-f9fd5a7d8a764d92ab3a820c935b39012020-11-24T21:35:10ZengMDPI AGEntropy1099-43002019-01-012112710.3390/e21010027e21010027Parameter Identification of Fractional-Order Discrete Chaotic SystemsYuexi Peng0Kehui Sun1Shaobo He2Dong Peng3School of Physics and Electronics, Central South University, Changsha 410083, ChinaSchool of Physics and Electronics, Central South University, Changsha 410083, ChinaSchool of Physics and Electronics, Central South University, Changsha 410083, ChinaSchool of Physics and Electronics, Central South University, Changsha 410083, ChinaResearch on fractional-order discrete chaotic systems has grown in recent years, and chaos synchronization of such systems is a new topic. To address the deficiencies of the extant chaos synchronization methods for fractional-order discrete chaotic systems, we proposed an improved particle swarm optimization algorithm for the parameter identification. Numerical simulations are carried out for the Hénon map, the Cat map, and their fractional-order form, as well as the fractional-order standard iterated map with hidden attractors. The problem of choosing the most appropriate sample size is discussed, and the parameter identification with noise interference is also considered. The experimental results demonstrate that the proposed algorithm has the best performance among the six existing algorithms and that it is effective even with random noise interference. In addition, using two samples offers the most efficient performance for the fractional-order discrete chaotic system, while the integer-order discrete chaotic system only needs one sample.http://www.mdpi.com/1099-4300/21/1/27parameter identificationparticle swarm optimizationfractional differencediscrete chaotic system |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yuexi Peng Kehui Sun Shaobo He Dong Peng |
spellingShingle |
Yuexi Peng Kehui Sun Shaobo He Dong Peng Parameter Identification of Fractional-Order Discrete Chaotic Systems Entropy parameter identification particle swarm optimization fractional difference discrete chaotic system |
author_facet |
Yuexi Peng Kehui Sun Shaobo He Dong Peng |
author_sort |
Yuexi Peng |
title |
Parameter Identification of Fractional-Order Discrete Chaotic Systems |
title_short |
Parameter Identification of Fractional-Order Discrete Chaotic Systems |
title_full |
Parameter Identification of Fractional-Order Discrete Chaotic Systems |
title_fullStr |
Parameter Identification of Fractional-Order Discrete Chaotic Systems |
title_full_unstemmed |
Parameter Identification of Fractional-Order Discrete Chaotic Systems |
title_sort |
parameter identification of fractional-order discrete chaotic systems |
publisher |
MDPI AG |
series |
Entropy |
issn |
1099-4300 |
publishDate |
2019-01-01 |
description |
Research on fractional-order discrete chaotic systems has grown in recent years, and chaos synchronization of such systems is a new topic. To address the deficiencies of the extant chaos synchronization methods for fractional-order discrete chaotic systems, we proposed an improved particle swarm optimization algorithm for the parameter identification. Numerical simulations are carried out for the Hénon map, the Cat map, and their fractional-order form, as well as the fractional-order standard iterated map with hidden attractors. The problem of choosing the most appropriate sample size is discussed, and the parameter identification with noise interference is also considered. The experimental results demonstrate that the proposed algorithm has the best performance among the six existing algorithms and that it is effective even with random noise interference. In addition, using two samples offers the most efficient performance for the fractional-order discrete chaotic system, while the integer-order discrete chaotic system only needs one sample. |
topic |
parameter identification particle swarm optimization fractional difference discrete chaotic system |
url |
http://www.mdpi.com/1099-4300/21/1/27 |
work_keys_str_mv |
AT yuexipeng parameteridentificationoffractionalorderdiscretechaoticsystems AT kehuisun parameteridentificationoffractionalorderdiscretechaoticsystems AT shaobohe parameteridentificationoffractionalorderdiscretechaoticsystems AT dongpeng parameteridentificationoffractionalorderdiscretechaoticsystems |
_version_ |
1725946313950887936 |