Download Modelling, Estimation and Control of Networked Complex by Arturo Buscarino, Luigi Fortuna, Mattia Frasca, Alessandro PDF

By Arturo Buscarino, Luigi Fortuna, Mattia Frasca, Alessandro Rizzo (auth.), Alessandro Chiuso, Luigi Fortuna, Mattia Frasca, Alessandro Rizzo, Luca Schenato, Sandro Zampieri (eds.)

The paradigm of complexity is pervading either technological know-how and engineering, resulting in the emergence of novel ways orientated on the improvement of a systemic view of the phenomena lower than learn; the definition of robust instruments for modelling, estimation, and keep watch over; and the cross-fertilization of alternative disciplines and ways. This publication is dedicated to networked structures that are the most promising paradigms of complexity. it really is established that advanced, dynamical networks are strong instruments to version, estimate, and regulate many fascinating phenomena, like agent coordination, synchronization, social and economics occasions, networks of severe infrastructures, assets allocation, details processing, or regulate over verbal exchange networks. in addition, it truly is proven how the hot technological advances in instant verbal exchange and reducing in fee and dimension of digital units are selling the looks of huge reasonably cheap interconnected structures, each one with computational, sensing and cellular features.

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Synchronization of moving chaotic agents. Physical Review Letters 100(4), 044, 102 (2008) 23. : Paths to synchronization on complex networks. Physical Review Letters 98, 034,101 (2007) 24. : Modified method for synchronizing and cascading chaotic systems. Physical Review E 52, R2145–R2148 (1995) 25. : Synchronization of chaos using continuous control. Physical Review E 50, 1642–1644 (1994) 26. : General approach for chaotic synchronization with applications to communication. Physical Review Letters 74, 5028–5031 (1995) 27.

Thus, the numerical analysis seems to indicate that the presented adaptive strategies are strongly robust to topological variations. In fact, a sufficient condition for synchronization seems to be that the time-varying Laplacian always remains connected. The analytical proof of asymptotic stability in this case is currently under investigation. 6 Conclusions In this chapter we discussed a novel decentralized adaptive strategy to synchronize complex networks. We presented two alternative strategies.

1. The simulation shown in Fig. 2 confirms the effectiveness of such strategy in achieving synchronization while guaranteeing that all coupling gains converge towards some constant values. 2 0 0 2 4 35 σi(t) xi(t) 2 t t 6 8 6 8 Fig. 7): evolution of xi (top) and σi (bottom). 2 0 0 2 4 σij(t) pi(t) 400 200 0 −200 −400 0 t t 6 8 6 8 Fig. 10): evolution of xi (top) and σi (bottom). 2 Network of N Identical Chua’s Circuits The synchronization of networks of Chua’s circuits [18] has been widely investigated in the existing literature on synchronization (see for instance [6, 7, 2, 31, 30] and references therein).

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