Adaptive Feedback Stabilization with Quantized State Measurements for a Class of Chaotic Systems

Wang, Yinhe; Fan, Yongqing; Wang, Qingyun; Zhang, Yun

doi:10.1088/0253-6102/57/5/11

Cited by 4 publications

(2 citation statements)

References 17 publications

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“…The results show that the time-varying quantizing methods can stabilizing nonlinear systems better than the static quantization approaches. Inspired by the corresponding results in [17][18][19], a new adaptive nonlinear controller is designed to feedback stabilize a class of new chaotic systems in which the nonlinear terms are monotonically increasing odd functions with the range [−1, 1].…”

Section: Introductionmentioning

confidence: 99%

Stabilization for a Class of New Chaotic Systems with Adaptive Quantizer

Zhai¹,

Wang²

2015

Proceedings of the 2015 International Conference on Electrical, Automation and Mechanical Engineering

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Abstract-This paper investigates the asymptotical stabilization via state feedback for a class of new chaotic systems, which nonlinear terms are monotonically increasing odd functions with the range [−1, 1], with a quantizer connected on the input channel. The updated law and adaptive law of estimate boundary error of quantizer are derived firstly. By the help of it, the nonlinear adaptive controller is proposed to ensure the chaotic system to be stabilized asymptotically. A simulation example is utilized to demonstrate the validity of the results in this paper.

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Section: Introductionmentioning

confidence: 99%

Stabilization for a Class of New Chaotic Systems with Adaptive Quantizer

Zhai¹,

Wang²

2015

Proceedings of the 2015 International Conference on Electrical, Automation and Mechanical Engineering

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“…Nowadays, whereas chaos control and synchronization of integer‐order chaotic systems have been extensively studied , chaos control and synchronization of their fractional‐order counterparts have been investigated only recently. It is still considered a challenging research topic.…”

Section: Introductionmentioning

confidence: 99%

Tensor Product Model Transformation Based Control and Synchronization of a Class of Fractional‐Order Chaotic Systems

Kuntanapreeda¹

2014

Asian Journal of Control

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Fractional‐order chaotic systems are the complex systems that involve non‐integer order derivatives. In this paper, tensor product (TP) model transformation‐based controller design for control and synchronization of a class of the fractional‐order chaotic systems is investigated. We propose a novel linear matrix inequality (LMI)‐based stabilization condition for fractional‐order TP models with a controller derived via a parallel distributed compensation (PDC) structure. In the controller design, the controlled system first is transformed into a convex state‐space TP model using the TP model transformation. Based on the transformed TP model, the controller is determined by solving the proposed LMI condition. To the best of our knowledge, this is the first investigation of TP model transformation based design in fractional‐order systems. Several illustrative examples are given to demonstrate the convenience of the proposed LMI condition and the effectiveness of the controller design.

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Projective synchronization of two different fractional-order chaotic systems via adaptive fuzzy control

Bouzeriba

Boulkroune

Bouden

2015

Neural Comput & Applic

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In this paper, the projective synchronization problem of two fractional-order different chaotic (or hyperchaotic) systems with both uncertain dynamics and external disturbances is considered. More particularly, a fuzzy adaptive control system is investigated for achieving an appropriate projective synchronization of unknown fractional-order chaotic systems. The adaptive fuzzy logic systems are used to approximate some uncertain nonlinear functions appearing in the system model. These latter are augmented by a robust control term to compensate for the unavoidable fuzzy approximation errors and external disturbances as well as residual error due to the use of the socalled e-modification in the adaptive laws. A Lyapunov approach is adopted for the design of the parameter adaptation laws and the proof of the corresponding stability as well as the asymptotic convergence of the underlying synchronization errors towards zero. The effectiveness of the proposed synchronization system is illustrated through numerical experiment results.

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Adaptive Feedback Stabilization with Quantized State Measurements for a Class of Chaotic Systems

Cited by 4 publications

References 17 publications

Stabilization for a Class of New Chaotic Systems with Adaptive Quantizer

Stabilization for a Class of New Chaotic Systems with Adaptive Quantizer

Tensor Product Model Transformation Based Control and Synchronization of a Class of Fractional‐Order Chaotic Systems

Projective synchronization of two different fractional-order chaotic systems via adaptive fuzzy control

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