Synchronization of complex dynamical networks via pinning scheme design under hybrid topologies

Yu, Rui; Zhang, Huaguang; Wang, Zhiliang; Wang, Junyi

doi:10.1016/j.neucom.2016.05.086

Cited by 7 publications

(5 citation statements)

References 40 publications

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“…Theorem 1: Given the probability density function of the multivariate output of local subsystem i defined in Equation (5), the probability density function of the randomized controller of subsystem i defined in Equation (9), and Definition 1, the probabilistic message to be passed from subsystem i about a subset q of its internal states to subsystem j is given by, M j←i (y q t;i z t−1;i ) = N (µ q y t;i , q y t;i ),…”

Section: A Probabilistic Message Passingmentioning

confidence: 99%

“…where t;j and ν t;j are Gaussian noises with zero means and Q j and R j covariances respectively as can be inferred from Equation (5). The optimized randomized controller for the subsystems in the proposed decentralized control framework is defined in Equation (9). Based on (9), the stochastic representation of the randomized controller of subsystem j is given by, u t;j =ū t;j + η t;j ,…”

Section: Stochastic Controllabilitymentioning

confidence: 99%

“…Current advances include, multiagent systems [4], distributed control [5], [6], pinning control [7]- [9] and decentralized control [10], [11] to name a few. These advances however suffer from either over-representing single-agent architectures as far as the controller design is concerned, which are centralized and so complete observation of the global state must be known, or are decentralized and decisions are based only on incomplete and disconnected…”

Section: Introductionmentioning

confidence: 99%

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Probabilistic Message Passing for Decentralized Control of Stochastic Complex Systems

Herzallah

2019

IEEE Access

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This paper proposes a novel probabilistic framework for the design of probabilistic message passing mechanism for complex and large dynamical systems that are operating and governing under a decentralized way. The proposed framework considers the evaluation of probabilistic messages that can be passed between mutually interacting quasi-independent subsystems that will not be restricted by the assumption of homogeneity or conformability of the subsystems components. The proposed message passing scheme is based on the evaluation of the marginal density functions of the states that need to be passed from one subsystem to another. An additional contribution is the development of stochastic controllability analysis of the controlled subsystems that constitute a complex system. To facilitate the understanding and the analytical analysis of the proposed message passing mechanism and the controllability analysis, theoretical developments are demonstrated on linear stochastic Gaussian systems.INDEX TERMS Probabilistic control, probabilistic message passing, stochastic systems.

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Section: A Probabilistic Message Passingmentioning

confidence: 99%

Section: Stochastic Controllabilitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Probabilistic Message Passing for Decentralized Control of Stochastic Complex Systems

Herzallah

2019

IEEE Access

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Section: Introductionmentioning

confidence: 99%

Probabilistic Message Passing for Decentralized Control of Stochastic Complex Systems

Herzallah¹

2020

Preprint

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<pre>This paper proposes a novel probabilistic framework for the design of probabilistic message passing mechanism for complex and large dynamical systems that are operating and governing under a decentralized way. The proposed framework considers the evaluation of probabilistic messages that can be passed between mutually interacting quasi-independent subsystems that will not be restricted by the assumption of homogeneity or conformability of the subsystems components. The proposed message passing scheme is based on the evaluation of the marginal density functions of the states that need to be passed from one subsystem to another. An additional contribution is the development of stochastic controllability analysis of the controlled subsystems that constitute a complex system. To facilitate the understanding and the analytical analysis of the proposed message passing mechanism and the controllability analysis, theoretical developments are demonstrated on linear stochastic Gaussian systems. </pre>

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“…It should be noted that, the system cannot usually synchronize without an external controller. Then, lots of effective control methods have been adopted to achieve synchronization, such as adaptive control , feedback control , pinned control , impulsive control , intermittent state feedback control and so on. For example, in , adaptive controllers and updating rules were designed according to the state information of its neighborhood, then the authors achieved the distributed synchronization of agent networks with nonlinearities via adaptive controllers.…”

Section: Introductionmentioning

confidence: 99%

Exponential Synchronization of Memristive Chaotic Recurrent Neural Networks Via Alternate Output Feedback Control

Fang

2017

Asian Journal of Control

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This paper considers the global exponential synchronization problem of two memristive chaotic recurrent neural networks with time-varying delays using periodically alternate output feedback control. First, the periodically alternate output feedback control rule is designed for the global exponential synchronization of two memristive chaotic recurrent neural networks. Then, according to the Lyapunov stability theory, we construct an appropriate Lyapunov-Krasovskii functional to derive several new sufficient conditions guaranteeing exponential synchronization of two memristive chaotic recurrent neural networks under periodically alternate output feedback control. Compared with existing results on synchronization conditions on the basis of linear matrix inequalities of memristive chaotic recurrent neural networks, the derived results complement, extend earlier related results, and are also easy to validate in this paper. An illustrative example is provided to illustrate the effectiveness of the synchronization criteria.

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Synchronization of complex dynamical networks via pinning scheme design under hybrid topologies

Cited by 7 publications

References 40 publications

Probabilistic Message Passing for Decentralized Control of Stochastic Complex Systems

Probabilistic Message Passing for Decentralized Control of Stochastic Complex Systems

Probabilistic Message Passing for Decentralized Control of Stochastic Complex Systems

Exponential Synchronization of Memristive Chaotic Recurrent Neural Networks Via Alternate Output Feedback Control

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