SYSYJul 11, 2017

On the stability and convergence of a class of consensus systems with a nonlinear input

arXiv:1506.014305 citations
AI Analysis

Provides theoretical guarantees for a specific class of consensus systems, but the results are incremental and domain-specific.

The paper derives conditions for stability and convergence of a class of consensus systems with nonlinear input, relevant to IoT applications, and provides a rigorous proof with an example from speed advisory systems.

We consider a class of consensus systems driven by a nonlinear input. Such systems arise in a class of IoT applications. Our objective in this paper is to determine conditions under which a certain partially distributed system converges to a Lur'e-like scalar system, and to provide a rigorous proof of its stability. Conditions are derived for the non-uniform convergence and stability of such a system and an example is given of a speed advisory system where such a system arises in real engineering practice.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes