Time-Delayed Feedback Control of Time-Delay Chaotic Systems

Guan, Xinping; Chen, Cailian; Peng, Haipeng; Fan, Zhencheng

doi:10.1142/s021812740300642x

Cited by 65 publications

(39 citation statements)

References 40 publications

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“…Secondly, we adopt a polynomial approximation of the Mackey-Glass system, which can be described by [20]: . The response system should be designed as:…”

Section: Examplementioning

confidence: 99%

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Synchronization of Time-Delay Chaotic System in Presence of Noise

Lei¹,

Peng²,

Yang³

et al. 2012

IJCIS

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Chaotic synchronization, as a key technique of chaotic secure communication, has received much attention in recent years. This paper proposes a nonlinear synchronization scheme for the time-delay chaotic system in the presence of noise. In this scheme, an integrator is introduced to suppress the influence of channel noise in the synchronization process. The experimental results demonstrate the effectiveness and feasibility of the proposed scheme which is strongly robust against noises, especially the high-frequency noises.

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“…Secondly, we adopt a polynomial approximation of the Mackey-Glass system, which can be described by [20]: . The response system should be designed as:…”

Section: Examplementioning

confidence: 99%

“…Finally, we consider the system with the following mathematical form [20]: . Accordingly, we design the response system as: From Figs.…”

Section: Examplementioning

confidence: 99%

Synchronization of Time-Delay Chaotic System in Presence of Noise

Lei¹,

Peng²,

Yang³

et al. 2012

IJCIS

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“…Under such a situation, the current state information of the drive chaotic system cannot be obtained to realize the synchronization. In [12]- [14], synchronization using time-delayed feedback control was investigated. Linear controller using constant time-delayed system state information of both drive and response chaotic system, and the current system state information of response chaotic system was proposed to realize the synchronization.…”

Section: Introductionmentioning

confidence: 99%

“…Linear controller using constant time-delayed system state information of both drive and response chaotic system, and the current system state information of response chaotic system was proposed to realize the synchronization. Both time-delay independent and dependent stability conditions were derived [12]- [14] using the Lyapunov-Krasovksii function. This delayed-feedback control approach was extended to adaptive fuzzy framework [15].…”

Section: Introductionmentioning

confidence: 99%

“…The time delay to be considered is time varying and uncertain in value. It is due to this reason, the proposed fuzzy state-feedback controller cannot use the time-delayed system state information of the response chaotic system compared to the linear control [12]- [14] and the adaptive fuzzy control [15] approaches of which constant time delay was considered. To cope with the time-varying delay, the boundedness property of the system states of the drive chaotic system is taken advantage to investigate system stability.…”

Section: Introductionmentioning

confidence: 99%

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Synchronization of Chaotic Systems Using Time-Delayed Fuzzy State-Feedback Controller

Lam

Ling

Lü³

et al. 2008

IEEE Trans. Circuits Syst. I

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Abstract-This paper presents the fuzzy-model-based control approach to synchronize two chaotic systems subject to parameter uncertainties. A fuzzy state-feedback controller using the system state of response chaotic system and the time-delayed system state of drive chaotic system is employed to realize the synchronization. The time delay which complicates the system dynamics makes the analysis difficult. To investigate the system stability and facilitate the design of fuzzy controller, T-S fuzzy models are employed to represent the system dynamics of the chaotic systems. Furthermore, the membership grades of the T-S fuzzy models become uncertain due to the existence of parameter uncertainties which further complicates the system analysis. To ease the stability analysis and produce less conservative analysis result, the membership functions of both T-S fuzzy models and fuzzy controller are considered. Stability conditions are derived using Lyapunov-based approach to aid the design of fuzzy state-feedback controller to synchronize the chaotic systems. Simulation examples are presented to illustrate the merits of the proposed approach.

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Adaptive actuator failure compensation design for unknown chaotic multi‐input systems

Tahoun

2014

Adaptive Control & Signal

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In this paper, an adaptive control approach is designed for compensating the faults in the actuators of chaotic systems and maintaining the acceptable system stability. We propose a state-feedback model reference adaptive control scheme for unknown chaotic multi-input systems. Only the dimensions of the chaotic systems are required to be known. Based on Lyapunov stability theory, new adaptive control laws are synthesized to accommodate actuator failures and system nonlinearities. An illustrative example is studied. The simulation results show the effectiveness of the design method.

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Time-Delayed Feedback Control of Time-Delay Chaotic Systems

Cited by 65 publications

References 40 publications

Synchronization of Time-Delay Chaotic System in Presence of Noise

Synchronization of Time-Delay Chaotic System in Presence of Noise

Synchronization of Chaotic Systems Using Time-Delayed Fuzzy State-Feedback Controller

Adaptive actuator failure compensation design for unknown chaotic multi‐input systems

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