An observer-based approach to controlling time-delay chaotic systems via Takagi–Sugeno fuzzy model

Ting, Chen‐Sheng

doi:10.1016/j.ins.2007.03.032

Cited by 42 publications

(19 citation statements)

References 18 publications

(33 reference statements)

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“…Remark 1 It can be easy shown that there are several chaotic systems which can be categorized in the form of (5), such as the Chua circuit [9] and the MackeyGlass model [27].…”

Section: Problem Statementmentioning

confidence: 99%

“…However, most of the chaotic systems have fixed time delay and they are satisfied in this assumption [7][8][9]. A2 and A3 are commonly considered to guarantee existence of the solution of the system (5).…”

Section: Problem Statementmentioning

confidence: 99%

“…This problem can be handled implicitly by using the observer systems. For example, a fuzzy observer-based adaptive control for the chaotic-fuzzy systems was proposed by Ting [9]. The work has solved the problems of synchronization, stabilization, and tracking control.…”

Section: Introductionmentioning

confidence: 99%

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Observer-based model reference adaptive control for unknown time-delay chaotic systems with input nonlinearity

2011

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Existence of unknown time-delay in the systems is a drastic restriction that it can menace the stability criteria and even deteriorate the performance system. This undesired case would be more intensified if that the uncertain input nonlinearity effects are also considered. To handle the input nonlinearities effects (results in dead-zone and/or hysteresis phenomena) and also unknown time-delay in the chaotic systems, this paper presents an observer-based Model Reference Adaptive Control (MRAC) scheme for a class of unknown time-delay chaotic systems with disturbances. This new method is a delay-independent variable-structure control method which is integrated with an observer system. The main task of the proposed approach is to accomplish a perfect tracking procedure such that unknown parameters are adapted via output estimation error. Furthermore, stability of the closed-loop system is achieved by means of the Lyapunov stability theory. Finally, the proposed methods are applied to some famous chaotic systems to verify the effectiveness of the proposed methods.

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“…Remark 1 It can be easy shown that there are several chaotic systems which can be categorized in the form of (5), such as the Chua circuit [9] and the MackeyGlass model [27].…”

Section: Problem Statementmentioning

confidence: 99%

Section: Problem Statementmentioning

confidence: 99%

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Observer-based model reference adaptive control for unknown time-delay chaotic systems with input nonlinearity

2011

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“…Sometimes, it is difficult to derive accurate analytical models in many real engineering systems especially when the plants to be controlled are complex in structure and operate under noisy environments [4,5]. An alternative is the use of intelligent controls based on soft computing schemes such as fuzzy logic (FL) and neural networks (NNs) [6][7][8]. FL systems, however, lack training capability to adapt themselves under new system conditions, whereas the NN-based reasoning is opaque to users.…”

Section: Introductionmentioning

confidence: 99%

A Neural Fuzzy System for Vibration Control in Flexible Structures

Wang

2011

ICA

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An adaptive neural fuzzy (NF) controller is developed in this paper for active vibration suppression in flexible structures. A recurrent identification network (RIN) is developed to adaptively identify system dynamics of the plant. A novel recurrent training (RT) technique is suggested to train the RIN so as to optimize nonlinear input-output mapping and to enhance convergence. The effectiveness of the developed controller and the related techniques has been verified experimentally corresponding to different control scenarios. Test results show that the proposed RIN can effectively recognize the time-varying dynamics of the plant. The RT-based hybrid training technique can improve the adaptive capability of the control system to accommodate different system conditions and enhance the training convergence. The developed NF controller is a robust and stable vibration suppression system, and it outperforms other related NF controllers.

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“…The TS fuzzy control theory has been applied to chaos control and synchronization in some literatures [24 -26]. Recently, the TS fuzzy model based approach to synchronization for time-delayed chaotic systems was proposed in [27].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy H_∞ Synchronization for Chaotic Systems with Time-Varying Delay

Ahn

2011

Zeitschrift Für Naturforschung A

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In this paper, we propose a new H ∞ synchronization method for fuzzy model based chaotic systems with external disturbance and time-varying delay. Based on Lyapunov-Krasovskii theory, TakagiSugeno (TS) fuzzy model, and linear matrix inequality (LMI) approach, the H ∞ synchronization controller is presented to not only guarantee stable synchronization but also reduce the effect of external disturbance to an H ∞ norm constraint. The proposed controller can be obtained by solving a convex optimization problem represented by the LMI. A simulation study is presented to demonstrate the validity of the proposed approach.

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An observer-based approach to controlling time-delay chaotic systems via Takagi–Sugeno fuzzy model

Cited by 42 publications

References 18 publications

Observer-based model reference adaptive control for unknown time-delay chaotic systems with input nonlinearity

Observer-based model reference adaptive control for unknown time-delay chaotic systems with input nonlinearity

A Neural Fuzzy System for Vibration Control in Flexible Structures

Fuzzy H_∞ Synchronization for Chaotic Systems with Time-Varying Delay

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An observer-based approach to controlling time-delay chaotic systems via Takagi–Sugeno fuzzy model

Cited by 42 publications

References 18 publications

Observer-based model reference adaptive control for unknown time-delay chaotic systems with input nonlinearity

Observer-based model reference adaptive control for unknown time-delay chaotic systems with input nonlinearity

A Neural Fuzzy System for Vibration Control in Flexible Structures

Fuzzy H∞ Synchronization for Chaotic Systems with Time-Varying Delay

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Product

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Fuzzy H_∞ Synchronization for Chaotic Systems with Time-Varying Delay