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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Main Authors: Yuexi Peng, Kehui Sun, Shaobo He, Dong Peng
Format: Article
Language:English
Published: MDPI AG 2019-01-01
Series:Entropy
Subjects:
Online Access:http://www.mdpi.com/1099-4300/21/1/27
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spelling 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
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