A Nonlinear Convergence Consensus: Extreme Doubly Stochastic Quadratic Operators for Multi-Agent Systems

A Nonlinear Convergence Consensus: Extreme Doubly Stochastic Quadratic Operators for Multi-Agent Systems

We investigate a novel nonlinear consensus from the extreme points of doubly stochastic quadratic operators (EDSQO), based on majorization theory and Markov chains for time-varying multi-agent distributed systems. We describe a dynamic system that has a local interaction network among agents. EDSQO...

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Bibliographic Details
Main Authors: Rawad Abdulghafor, Sultan Almotairi, Hamad Almohamedh, Badr Almutairi, Abdullah Bajahzar, Sulaiman Sulmi Almutairi
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Symmetry
Subjects:
nonlinear consensus
multi-agent systems
extreme doubly stochastic quadratic operators
finite dimensional stochastic matrix
convergence
Online Access:https://www.mdpi.com/2073-8994/12/4/540

Internet

https://www.mdpi.com/2073-8994/12/4/540

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