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
Esta investigação aplica o observador neural difuso adaptativo (AFNO) para sincronizar uma classe de sistemas caóticos desconhecidos apenas através de sinal de transmissão escalar. O método proposto pode ser usado em sincronização se sistemas caóticos não lineares puderem ser transformados na forma canônica do tipo sistema Lur'e pelo método geométrico diferencial. Nesta abordagem, a rede neural difusa adaptativa (FNN) no AFNO é adotada on-line para modelar o termo não linear no transmissor. Além disso, os estados desconhecidos do mestre podem ser reconstruídos a partir de um estado transmitido usando o design do observador na extremidade do escravo. A sincronização é alcançada quando todos os estados são observados. O esquema utilizado pode estimar adaptativamente os estados do transmissor on-line, mesmo se o transmissor for alterado para outro sistema de caos. Por outro lado, a robustez do AFNO pode ser garantida em relação ao erro de modelagem e à perturbação externa limitada. Os resultados da simulação confirmam que o projeto AFNO é válido para a aplicação de sincronização de caos.
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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},}
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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 -