Chaos Synchronization Based on Unknown Input Proportional Multiple-Integral Fuzzy Observer
This paper presents an unknown input Proportional Multiple-Integral Observer (PIO) for synchronization of chaotic systems based on Takagi-Sugeno (TS) fuzzy chaotic models subject to unmeasurable decision variables and unknown input. In a secure communication configuration, this unknown input is rega...
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Series: | Abstract and Applied Analysis |
Online Access: | http://dx.doi.org/10.1155/2013/670878 |
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doaj-bdf42aa0ff2649a6b58ea6e00a2df0152020-11-24T23:48:41ZengHindawi LimitedAbstract and Applied Analysis1085-33751687-04092013-01-01201310.1155/2013/670878670878Chaos Synchronization Based on Unknown Input Proportional Multiple-Integral Fuzzy ObserverT. Youssef0M. Chadli1H. R. Karimi2M. Zelmat3Laboratory of Modeling, Information & Systems (MIS), University of Picardie Jules Verne (UPJV), 33 rue Saint Leu, 80039 Amiens Cedex 1, FranceLaboratory of Modeling, Information & Systems (MIS), University of Picardie Jules Verne (UPJV), 33 rue Saint Leu, 80039 Amiens Cedex 1, FranceDepartment of Engineering, Faculty of Engineering and Science, University of Agder, 4898 Grimstad, NorwayLaboratory of Automatic Applied (LAA), M’hamed Bougara University of Boumerdès (UMBB), 35000 Boumerdès, AlgeriaThis paper presents an unknown input Proportional Multiple-Integral Observer (PIO) for synchronization of chaotic systems based on Takagi-Sugeno (TS) fuzzy chaotic models subject to unmeasurable decision variables and unknown input. In a secure communication configuration, this unknown input is regarded as a message encoded in the chaotic system and recovered by the proposed PIO. Both states and outputs of the fuzzy chaotic models are subject to polynomial unknown input with kth derivative zero. Using Lyapunov stability theory, sufficient design conditions for synchronization are proposed. The PIO gains matrices are obtained by resolving linear matrix inequalities (LMIs) constraints. Simulation results show through two TS fuzzy chaotic models the validity of the proposed method.http://dx.doi.org/10.1155/2013/670878 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
T. Youssef M. Chadli H. R. Karimi M. Zelmat |
spellingShingle |
T. Youssef M. Chadli H. R. Karimi M. Zelmat Chaos Synchronization Based on Unknown Input Proportional Multiple-Integral Fuzzy Observer Abstract and Applied Analysis |
author_facet |
T. Youssef M. Chadli H. R. Karimi M. Zelmat |
author_sort |
T. Youssef |
title |
Chaos Synchronization Based on Unknown Input Proportional Multiple-Integral Fuzzy Observer |
title_short |
Chaos Synchronization Based on Unknown Input Proportional Multiple-Integral Fuzzy Observer |
title_full |
Chaos Synchronization Based on Unknown Input Proportional Multiple-Integral Fuzzy Observer |
title_fullStr |
Chaos Synchronization Based on Unknown Input Proportional Multiple-Integral Fuzzy Observer |
title_full_unstemmed |
Chaos Synchronization Based on Unknown Input Proportional Multiple-Integral Fuzzy Observer |
title_sort |
chaos synchronization based on unknown input proportional multiple-integral fuzzy observer |
publisher |
Hindawi Limited |
series |
Abstract and Applied Analysis |
issn |
1085-3375 1687-0409 |
publishDate |
2013-01-01 |
description |
This paper presents an unknown input Proportional Multiple-Integral Observer (PIO) for synchronization of chaotic systems based on Takagi-Sugeno (TS) fuzzy chaotic models subject to unmeasurable decision variables and unknown input. In a secure communication configuration, this unknown input is regarded as a message encoded in the chaotic system and recovered by the proposed PIO. Both states and outputs of the fuzzy chaotic models are subject to polynomial unknown input with kth derivative zero. Using Lyapunov stability theory, sufficient design conditions for synchronization are proposed. The PIO gains matrices are obtained by resolving linear matrix inequalities (LMIs) constraints. Simulation results show through two TS fuzzy chaotic models the validity of the proposed method. |
url |
http://dx.doi.org/10.1155/2013/670878 |
work_keys_str_mv |
AT tyoussef chaossynchronizationbasedonunknowninputproportionalmultipleintegralfuzzyobserver AT mchadli chaossynchronizationbasedonunknowninputproportionalmultipleintegralfuzzyobserver AT hrkarimi chaossynchronizationbasedonunknowninputproportionalmultipleintegralfuzzyobserver AT mzelmat chaossynchronizationbasedonunknowninputproportionalmultipleintegralfuzzyobserver |
_version_ |
1725485099737153536 |