Mean sqaure synchronization in large scale nonlinear networks with uncertain links
Amit Diwadkar, Umesh Vaidya

TL;DR
This paper develops a stochastic synchronization framework for large nonlinear networks with uncertain links, introducing a stochastic Positive Real Lemma and analyzing eigenvalue roles in synchronization.
Contribution
It introduces a stochastic Positive Real Lemma and provides new synchronization conditions considering link uncertainty and eigenvalues, with analytical tradeoffs for torus topologies.
Findings
Both largest and second smallest Laplacian eigenvalues influence synchronization.
Derived a margin of synchronization based on control theory.
Validated results through simulations of coupled oscillators.
Abstract
In this paper, we study the problem of synchronization with stochastic interaction among network components. The network components dynamics is nonlinear and modeled in Lure form with linear stochastic interaction among network components. To study this problem we first prove the stochastic version of Positive Real Lemma (PRL). The stochastic PRL result is then used to provide sufficient condition for synchronization of stochastic network system. The sufficiency condition for synchronization, is a function of nominal (mean) coupling Laplacian eigenvalues and the statistics of link uncertainty in the form of coefficient of dispersion (CoD). Contrary to the existing literature on network synchronization, our results indicate that both the largest and the second smallest eigenvalue of the mean Laplacian play an important role in synchronization of stochastic networks. Robust control-based…
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Taxonomy
TopicsNeural Networks Stability and Synchronization · Distributed Control Multi-Agent Systems · Nonlinear Dynamics and Pattern Formation
