Adaptive lag synchronization based topology identification scheme of uncertain general complex dynamical networks

Che, Yanqiu; Li, Ruixue; Wang, J.; Cui, Shigang; Deng, Bin; Wei, Xile

doi:10.1140/epjb/e2012-20959-7

Cited by 20 publications

(17 citation statements)

References 30 publications

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“…Therefore, topology detection of complex dynamical networks [21][22][23][24][25][26][27][28][29] has become a significant topic for further studies. It is functionally powerful to employ the adaptive feedback control strategy to the structure detection of complex networks [21,22,[24][25][26][27][28]. The target topology matrix which Zhou and Lu [21] considered was not needed to be symmetric, irreducible, or diffusive.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, the inevitable transmission delay in reality is always hard to determine. Based on the statecoupling network model, the unknown network structure was obtained by achieving the lag synchronization between drive and response systems [28]. In their scheme, all states of nodes were transmitted for the synchronization of full statecoupling complex networks.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Topology Detection for Output‐Coupling Weighted Complex Dynamical Networks with Coupling and Transmission Delays

Wang

Jiang

Cheng

et al. 2017

Mathematical Problems in Engineering

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Topology detection for output-coupling weighted complex dynamical networks with two types of time delays is investigated in this paper. Different from existing literatures, coupling delay and transmission delay are simultaneously taken into account in the output-coupling network. Based on the idea of the state observer, we build the drive-response system and apply LaSalle's invariance principle to the error dynamical system of the drive-response system. Several convergent criteria are deduced in the form of algebraic inequalities. Some numerical simulations for the complex dynamical network, with node dynamics being chaotic, are given to verify the effectiveness of the proposed scheme.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Topology Detection for Output‐Coupling Weighted Complex Dynamical Networks with Coupling and Transmission Delays

Wang

Jiang

Cheng

et al. 2017

Mathematical Problems in Engineering

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“…Xu et al proposed an approach to identify the topological structure and unknown parameters for uncertain general complex networks with non-derivative and derivative couplings [35]. Exponentially adaptive synchronization, adaptive lag synchronization and generalized synchronization of uncertain general complex networks were studied in [36][37][38]. Che et al studied the anticipatory synchronization of uncertain nonlinearly coupled complex networks with time delays [39].…”

Section: Introductionmentioning

confidence: 99%

Exponential Outer Synchronization between Two Uncertain Time-Varying Complex Networks with Nonlinear Coupling

Liu

2015

Entropy

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This paper studies the problem of exponential outer synchronization between two uncertain nonlinearly coupled complex networks with time delays. In order to synchronize uncertain complex networks, an adaptive control scheme is designed based on the Lyapunov stability theorem. Simultaneously, the unknown system parameters of uncertain complex networks are identified when exponential outer synchronization occurs. Finally, numerical examples are provided to demonstrate the feasibility and effectiveness of the theoretical results.

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“…On the other hand, environmental uncertainty, always modeled by random noise, is also an inherent ingredient in complex networks. Now, identifying parameters and topology in time-delayed networks under noise circumstance has gradually attracted much research interest [22][23][24][25][26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Revealing network topology and dynamical parameters in delay-coupled complex network subjected to random noise

Yang

Wei

2015

Nonlinear Dyn

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It is well known that random noise and time delay are two inherent ingredients in complex networks, whose dynamical parameters and topological structures are often unknown or uncertain. This paper will employ the techniques of impulsive control and adaptive control to infer dynamical parameters and network topology in delay-coupled complex network under circumstance noise. By constructing an appropriate adaptive-impulsive control strategy in the response network, the unknown dynamical parameters and topology structure contained in the drive network are to be accurately identified; moreover, these two networks will achieve the global exponential synchronization in mean square. Based on the comparison theorem of impulsive differential equations, the accuracy of the proposed identification strategy is rigorously proved. Finally, two examples with networks of chaotic oscillators are presented to illustrate the application of the suggested strategy. Meanwhile, numerical results indicate that our proposed scheme is robust against the impulsive gain, the update gain and the network topology.

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Adaptive lag synchronization based topology identification scheme of uncertain general complex dynamical networks

Cited by 20 publications

References 30 publications

Topology Detection for Output‐Coupling Weighted Complex Dynamical Networks with Coupling and Transmission Delays

Topology Detection for Output‐Coupling Weighted Complex Dynamical Networks with Coupling and Transmission Delays

Exponential Outer Synchronization between Two Uncertain Time-Varying Complex Networks with Nonlinear Coupling

Revealing network topology and dynamical parameters in delay-coupled complex network subjected to random noise

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