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
Neste artigo, a fim de controlar sistemas caóticos incertos, um esquema de controle fuzzy adaptativo (AFC) é desenvolvido para as plantas multi-entradas/multi-saídas representadas pelos modelos fuzzy Takagi-Sugeno (TS). O esquema AFC proposto fornece rastreamento robusto de um sinal desejado para sistemas fuzzy TS com parâmetros incertos. A lei de controle desenvolvida e a lei adaptativa garantem a limitação de todos os sinais no sistema em malha fechada. Além disso, o estado caótico rastreia o estado do modelo de referência estável (SRM) assintoticamente com o tempo para qualquer sinal de entrada de referência limitado. A técnica de projeto AFC sugerida é aplicada ao controle de um sistema Lorenz incerto baseado no modelo fuzzy TS, como estabilização, sincronização e modelo caótico seguindo controle (CMFC).
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Chang-Woo PARK, Chang-Hoon LEE, Jung-Hwan KIM, Mignon PARK, "Adaptive Control of Uncertain Chaotic Systems Based on Takagi-Sugeno Fuzzy Models" in IEICE TRANSACTIONS on Fundamentals,
vol. E84-A, no. 9, pp. 2101-2117, September 2001, doi: .
Abstract: In this paper, in order to control uncertain chaotic system, an adaptive fuzzy control (AFC) scheme is developed for the multi-input/multi-output plants represented by the Takagi-Sugeno (T-S) fuzzy models. The proposed AFC scheme provides robust tracking of a desired signal for the T-S fuzzy systems with uncertain parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the chaotic state tracks the state of the stable reference model (SRM) asymptotically with time for any bounded reference input signal. The suggested AFC design technique is applied to control of a uncertain Lorenz system based on T-S fuzzy model such as stabilization, synchronization and chaotic model following control (CMFC).
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e84-a_9_2101/_p
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@ARTICLE{e84-a_9_2101,
author={Chang-Woo PARK, Chang-Hoon LEE, Jung-Hwan KIM, Mignon PARK, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Adaptive Control of Uncertain Chaotic Systems Based on Takagi-Sugeno Fuzzy Models},
year={2001},
volume={E84-A},
number={9},
pages={2101-2117},
abstract={In this paper, in order to control uncertain chaotic system, an adaptive fuzzy control (AFC) scheme is developed for the multi-input/multi-output plants represented by the Takagi-Sugeno (T-S) fuzzy models. The proposed AFC scheme provides robust tracking of a desired signal for the T-S fuzzy systems with uncertain parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the chaotic state tracks the state of the stable reference model (SRM) asymptotically with time for any bounded reference input signal. The suggested AFC design technique is applied to control of a uncertain Lorenz system based on T-S fuzzy model such as stabilization, synchronization and chaotic model following control (CMFC).},
keywords={},
doi={},
ISSN={},
month={September},}
Copiar
TY - JOUR
TI - Adaptive Control of Uncertain Chaotic Systems Based on Takagi-Sugeno Fuzzy Models
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2101
EP - 2117
AU - Chang-Woo PARK
AU - Chang-Hoon LEE
AU - Jung-Hwan KIM
AU - Mignon PARK
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E84-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2001
AB - In this paper, in order to control uncertain chaotic system, an adaptive fuzzy control (AFC) scheme is developed for the multi-input/multi-output plants represented by the Takagi-Sugeno (T-S) fuzzy models. The proposed AFC scheme provides robust tracking of a desired signal for the T-S fuzzy systems with uncertain parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the chaotic state tracks the state of the stable reference model (SRM) asymptotically with time for any bounded reference input signal. The suggested AFC design technique is applied to control of a uncertain Lorenz system based on T-S fuzzy model such as stabilization, synchronization and chaotic model following control (CMFC).
ER -