Convergence and Synchronization in Networks of Piecewise-Smooth Systems via Distributed Discontinuous Coupling
This work provides a theoretical framework for synchronization in networks of piecewise-smooth systems, which are common in engineering and biology, but the results are incremental as they extend existing diffusive coupling methods.
The paper addresses the gap in proving asymptotic convergence in networks of piecewise-smooth systems, proposing a distributed discontinuous coupling action to enforce global asymptotic state-synchronization. Analytical thresholds for coupling gains are provided, and a new connectivity measure (minimum density) is introduced.
Complex networks are a successful framework to describe collective behaviour in many applications, but a notable gap remains in the current literature, that of proving asymptotic convergence in networks of piecewise-smooth systems. Indeed, a wide variety of physical systems display discontinuous dynamics that change abruptly, including dry friction mechanical oscillators, electrical power converters, and biological neurons. In this paper, we study how to enforce global asymptotic state-synchronization in these networks. Specifically, we propose the addition of a distributed discontinuous coupling action to the commonly used diffusive coupling protocol. Moreover, we provide analytical estimates of the thresholds on the coupling gains required for convergence, and highlight the importance of a new connectivity measure, which we named minimum density. The theoretical results are illustrated by a set of representative examples.