Pinning Controllability of Complex Stochastic Networks

Burbano-L., Daniel A.; Russo, Giovanni; Bernardo, Mario di

doi:10.1016/j.ifacol.2017.08.1553

Cited by 9 publications

(4 citation statements)

References 30 publications

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“…Ongoing work is aimed at extending our approach to directed network topologies. Also, the effect of varying the topology of the noisy layer should be studied more in detail, since preliminary numerical results showed that this could enhance pinning controllability [28].…”

Section: Discussionmentioning

confidence: 99%

“…, and from Assumption 3.3 yields e G(e, t) ≥ k g e e so that e G(e, t) 2 ≥ 4(σ * k g ) 2 V (e). If condition (28) holds; then, condition (ii)-(iii) of Theorem 2.1 are fulfilled with c 3 > 2c 2 so that the closedloop network reaches complete stochastic synchronization onto x r and the proof is complete.…”

Section: Noise On the Node Dynamicsmentioning

confidence: 94%

“…When compared to previous literature, the work reported in this paper expands the state of the art in a number of different ways. In particular, (i) we study networks of diffusively coupled nodes affected by different types of possibly heterogeneous noise diffusion processes; (ii) our results, which are based on the use of stochastic Lyapunov functions, provide pinning controllability conditions in the case where only a fraction of the nodes is controlled; (iii) the nodes dynamics can be nonlinear, with their vector field satisfying the so-called QUAD (quadratic) condition, a more general condition than Lipschitz [27]; (iv) the coupling functions between nodes in the network can be nonlinear (preliminary results on networks with linear diffusive couplings were reported in [28]); and (v) under certain condition noise might be beneficial for enhancing the pinning controllability.…”

Section: A Related Workmentioning

confidence: 99%

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Pinning Controllability of Complex Network Systems With Noise

Burbano-L.

Russo

Bernardo

2019

IEEE Trans. Control Netw. Syst.

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The ability of a network of nonlinear systems to synchronize onto the desired reference trajectory in the presence of one or more leader nodes is known as the pinning controllability problem. This paper studies the pinning controllability of multi-agent networks subject to three different types of noise diffusion processes; namely, noise affecting the node dynamics, the communication links, and the pinning control action itself. By using appropriate stochastic Lyapunov functions, sufficient pinning controllability conditions are derived depending on the node dynamics, network structure, noise intensity, and control parameters. Counterintuitively, it is found that under some specific conditions noise may enhance the pinning controllability of the network making it easier to drive all agents towards the desired collective behavior. The effectiveness of the theoretical results is illustrated via two application examples arising in the context of gene regulatory networks and synchronization of chaotic systems.

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Section: Discussionmentioning

confidence: 99%

Section: Noise On the Node Dynamicsmentioning

confidence: 94%

Section: A Related Workmentioning

confidence: 99%

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Pinning Controllability of Complex Network Systems With Noise

Burbano-L.

Russo

Bernardo

2019

IEEE Trans. Control Netw. Syst.

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“…Thus, in the presence of external disturbances and control inputs, the equation of follower agents is given by system (2). The dynamic equation of the leader is as follows: According to [39,40], we show that the nonlinear term f (•) satisfies Assumption 1 when ρ 1 = 14.025. Since economic and financial systems are often subject to external disturbances due to environmental impacts, the unknown time-varying disturbance to the network is considered as follows:…”

Section: Model Descriptionmentioning

confidence: 99%

Stochastic Fixed-Time Tracking Control for the Chaotic Multi-Agent-Based Supply Chain Networks with Nonlinear Communication

et al. 2022

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The multi-agent-based supply chain network is a dynamic system consisting of multiple subchains connected by information flows, material flows and capital flow, etc. The consensus of multi-agent systems is often applied to the cooperation between subchains and inventory management in supply chain networks. Considering the ubiquitous external disturbances, this paper mainly considers the fixed-time consensus of a stochastic three-echelon multi-agent-based supply chain system. A nonlinear feedback fixed-time control protocol is constructed for ensuring the consensus of the considered supply chain network. Using the stability theory of stochastic differential equations, sufficient conditions for the fixed-time consensus and the upper bound estimation of the settling time are obtained. Finally, the validity of the control protocol and the correctness of the theoretical analysis are revealed by numerical simulation.

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