Complete synchronization, phase synchronization and parameters estimation in a realistic chaotic system

Ma, Jun; Fan, Liping; Huang, Long; Jin, Wuyin

doi:10.1016/j.cnsns.2010.12.030

Cited by 87 publications

(33 citation statements)

References 68 publications

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“…In this paper, it is assumed that all parameters can be obtained accurately. Future research will extend the proposed control method to high-order system with unknown parameters and improve it by introducing adjustable gain coefficient into controller, parameter observer and Lyapunov function similar to [58,59].…”

Section: Resultsmentioning

confidence: 98%

Fixed-time dynamic surface high-order sliding mode control for chaotic oscillation in power system

Liu

et al. 2016

Nonlinear Dyn

130

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In this paper, a fixed-time dynamic surface high-order sliding mode control approach is presented for chaos suppression and voltage stabilization in three-bus power system via design of current source converter-based static synchronous compensator controller. The proposed control strategy constructs two high-order sliding mode surfaces to achieve control objective. By combining backstepping idea with dynamic surface control (DSC) technique, highorder sliding mode controller is designed and the inherent problem of "explosion of complexity" in backstepping design is avoided. Further, a new stability concept is introduced into DSC design to achieve semiglobal uniform ultimate boundedness of the signals in high-order sliding mode system within finite time independent of initial condition. In addition, stability analysis is provided to show that the proposed control scheme can achieve semi-globally fixed-timely uniformly ultimately bounded stabilization. Finally, simulation results are given to demonstrate the effectiveness of the proposed control scheme and the superior performance over conventional DSC.

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Section: Resultsmentioning

confidence: 98%

Fixed-time dynamic surface high-order sliding mode control for chaotic oscillation in power system

Liu

et al. 2016

Nonlinear Dyn

130

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“…Since the seminal work of Pecora and Carroll [4], chaos synchronization has received a great deal of interest. The synchronization of chaos or hyperchaos is classified as complete synchronization [5,6], lag synchronization [7][8][9], generalized synchronization [10], and phase synchronization [11]. Transition of synchronization can be induced in the chaotic systems [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Chaos bursting synchronization of mismatched Hindmarsh–Rose systems via a single adaptive feedback controller

Wang

Shi

2011

Nonlinear Dyn

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Chaotic bursting synchronization of mismatched Hindmarsh-Rose neuron systems is investigated. Based on the Lyapunov stability theory, an adaptive feedback control scheme for the synchronization of the neuron systems is proposed when partially parameters of the response system are unknown and different with those of the drive system. Furthermore, in the proposed scheme, only a single adaptive feedback controller is needed, which is efficient and easy to implement. Finally, numerical simulations are provided to show the effectiveness of the developed methods.

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“…In the present paper, synchronization between two coupled neurons and between multiple neurons with different network connectivity patterns is studied Yu et al 2010;Che et al 2010;Hao et al 2010;Ma et al 2011;Haeri et al 2010;Gan et al 2011;Zheng and Lu 2008). There exist different connectivity patterns including ring-like neuronal network and grid-like neuronal network.…”

Section: Introductionmentioning

confidence: 99%

Synchronization study in ring-like and grid-like neuronal networks

Wang

et al. 2011

Cogn Neurodyn

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In this paper, we study the synchronization status of both two gap-junction coupled neurons and neuronal network with two different network connectivity patterns. One of the network connectivity patterns is a ring-like neuronal network, which only considers nearest-neighbor neurons. The other is a grid-like neuronal network, with all nearest neighbor couplings. We show that by varying some key parameters, such as the coupling strength and the external current injection, the neuronal network will exhibit various patterns of firing synchronization. Different types of firing synchronization are diagnosed by means of a mean field potential, a bifurcation diagram, a correlation coefficient and the ISI-distance method. Numerical simulations demonstrate that the synchronization status of multiple neurons is much dependent on the network patters, when the number of neurons is the same. It is also demonstrated that the synchronization status of two coupled neurons is similar with the grid-like neuronal network, but differs radically from that of the ring-like neuronal network. These results may be instructive in understanding synchronization transitions in neuronal systems.

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Complete synchronization, phase synchronization and parameters estimation in a realistic chaotic system

Cited by 87 publications

References 68 publications

Fixed-time dynamic surface high-order sliding mode control for chaotic oscillation in power system

Fixed-time dynamic surface high-order sliding mode control for chaotic oscillation in power system

Chaos bursting synchronization of mismatched Hindmarsh–Rose systems via a single adaptive feedback controller

Synchronization study in ring-like and grid-like neuronal networks

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