Adaptive Hybrid Function Projective Synchronization of Chaotic Systems with Time-Varying Parameters

The adaptive hybrid function projective synchronization (AHFPS) of different chaotic systems with unknown time-varying parameters is investigated. Based on the Lyapunov stability theory and adaptive bounding technique, the robust adaptive control law and the parameters update law are derived to make...

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Veröffentlicht in:Mathematical Problems in Engineering 2012-01, Vol.2012 (2012), p.95-112-407
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description The adaptive hybrid function projective synchronization (AHFPS) of different chaotic systems with unknown time-varying parameters is investigated. Based on the Lyapunov stability theory and adaptive bounding technique, the robust adaptive control law and the parameters update law are derived to make the states of two different chaotic systems asymptotically synchronized. In the control strategy, the parameters need not be known throughly if the time-varying parameters are bounded by the product of a known function of t and an unknown constant. In order to avoid the switching in the control signal, a modified robust adaptive synchronization approach with the leakage-like adaptation law is also proposed to guarantee the ultimately uni-formly boundedness (UUB) of synchronization errors. The schemes are successfully applied to the hybrid function projective synchronization between the Chen system and the Lorenz system and between hyperchaotic Chen system and generalized Lorenz system. Moreover, numerical simulation results are presented to verify the effectiveness of the proposed scheme.
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subjects Adaptive control
Adaptive control systems
Adaptive systems
Chaos theory
Chemical reactors
Communication
Control stability
Control theory
Economic models
Engineering
Hybrid systems
Law
Lorenz system
Mathematical analysis
Mathematical models
Neural networks
Parameter modification
Parameter robustness
Robust control
Studies
Synchronism
Synchronization
Time synchronization
title Adaptive Hybrid Function Projective Synchronization of Chaotic Systems with Time-Varying Parameters
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