The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Cette enquête applique l'observateur neuronal flou adaptatif (AFNO) pour synchroniser une classe de systèmes chaotiques inconnus via un signal de transmission scalaire uniquement. La méthode proposée peut être utilisée en synchronisation si les systèmes chaotiques non linéaires peuvent être transformés en la forme canonique du type système de Lur'e par la méthode géométrique différentielle. Dans cette approche, le réseau neuronal flou adaptatif (FNN) dans AFNO est adopté en ligne pour modéliser le terme non linéaire dans l'émetteur. De plus, les états inconnus du maître peuvent être reconstruits à partir d'un état transmis à l'aide d'une conception d'observateur du côté esclave. La synchronisation est obtenue lorsque tous les états sont observés. Le schéma utilisé peut estimer de manière adaptative les états de l'émetteur en ligne, même si l'émetteur est transformé en un autre système chaotique. D’un autre côté, la robustesse d’AFNO peut être garantie vis-à-vis de l’erreur de modélisation et des perturbations externes bornées. Les résultats de simulation confirment que la conception AFNO est valide pour l'application de la synchronisation du chaos.
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Bing-Fei WU, Li-Shan MA, Jau-Woei PERNG, "Observer-Based Synchronization for a Class of Unknown Chaos Systems with Adaptive Fuzzy-Neural Network" in IEICE TRANSACTIONS on Fundamentals,
vol. E91-A, no. 7, pp. 1797-1805, July 2008, doi: 10.1093/ietfec/e91-a.7.1797.
Abstract: This investigation applies the adaptive fuzzy-neural observer (AFNO) to synchronize a class of unknown chaotic systems via scalar transmitting signal only. The proposed method can be used in synchronization if nonlinear chaotic systems can be transformed into the canonical form of Lur'e system type by the differential geometric method. In this approach, the adaptive fuzzy-neural network (FNN) in AFNO is adopted on line to model the nonlinear term in the transmitter. Additionally, the master's unknown states can be reconstructed from one transmitted state using observer design in the slave end. Synchronization is achieved when all states are observed. The utilized scheme can adaptively estimate the transmitter states on line, even if the transmitter is changed into another chaos system. On the other hand, the robustness of AFNO can be guaranteed with respect to the modeling error, and external bounded disturbance. Simulation results confirm that the AFNO design is valid for the application of chaos synchronization.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e91-a.7.1797/_p
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@ARTICLE{e91-a_7_1797,
author={Bing-Fei WU, Li-Shan MA, Jau-Woei PERNG, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Observer-Based Synchronization for a Class of Unknown Chaos Systems with Adaptive Fuzzy-Neural Network},
year={2008},
volume={E91-A},
number={7},
pages={1797-1805},
abstract={This investigation applies the adaptive fuzzy-neural observer (AFNO) to synchronize a class of unknown chaotic systems via scalar transmitting signal only. The proposed method can be used in synchronization if nonlinear chaotic systems can be transformed into the canonical form of Lur'e system type by the differential geometric method. In this approach, the adaptive fuzzy-neural network (FNN) in AFNO is adopted on line to model the nonlinear term in the transmitter. Additionally, the master's unknown states can be reconstructed from one transmitted state using observer design in the slave end. Synchronization is achieved when all states are observed. The utilized scheme can adaptively estimate the transmitter states on line, even if the transmitter is changed into another chaos system. On the other hand, the robustness of AFNO can be guaranteed with respect to the modeling error, and external bounded disturbance. Simulation results confirm that the AFNO design is valid for the application of chaos synchronization.},
keywords={},
doi={10.1093/ietfec/e91-a.7.1797},
ISSN={1745-1337},
month={July},}
Copier
TY - JOUR
TI - Observer-Based Synchronization for a Class of Unknown Chaos Systems with Adaptive Fuzzy-Neural Network
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1797
EP - 1805
AU - Bing-Fei WU
AU - Li-Shan MA
AU - Jau-Woei PERNG
PY - 2008
DO - 10.1093/ietfec/e91-a.7.1797
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E91-A
IS - 7
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - July 2008
AB - This investigation applies the adaptive fuzzy-neural observer (AFNO) to synchronize a class of unknown chaotic systems via scalar transmitting signal only. The proposed method can be used in synchronization if nonlinear chaotic systems can be transformed into the canonical form of Lur'e system type by the differential geometric method. In this approach, the adaptive fuzzy-neural network (FNN) in AFNO is adopted on line to model the nonlinear term in the transmitter. Additionally, the master's unknown states can be reconstructed from one transmitted state using observer design in the slave end. Synchronization is achieved when all states are observed. The utilized scheme can adaptively estimate the transmitter states on line, even if the transmitter is changed into another chaos system. On the other hand, the robustness of AFNO can be guaranteed with respect to the modeling error, and external bounded disturbance. Simulation results confirm that the AFNO design is valid for the application of chaos synchronization.
ER -