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).
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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},}
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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 -