IIUM Repository

The convergence consensus of multi-agent systems controlled via doubly stochastic quadratic operators

Abdulghafor, Rawad and Sherzod Turaev, Sherzod and Zeki, Akram M. and Shahidi, Farruh (2016) The convergence consensus of multi-agent systems controlled via doubly stochastic quadratic operators. In: 1st International Symposium on Agents, Multi-Agent Systems and Robotics, ISAMSR 2015, 18 August 2015 - 19 August 2015, Putrajaya, Malaysia.

[img] PDF - Published Version
Restricted to Repository staff only

Download (641kB) | Request a copy
[img] PDF (SCOPUS) - Published Version
Restricted to Repository staff only

Download (749kB) | Request a copy

Abstract

This paper proposed doubly stochastic quadratic operators (DSQOs) for a consensus problem in multi-Agent systems. The proposed scheme uses new nonlinear class model of family of quadratic stochastic operators (QSOs) for convergence consensus. The nonlinear model of QSOs plays an important role for reaching consensus. The nonlinear protocols for DSQOs are based on majorization theory. The paper investigates how the multi-Agent systems converge to the optimal values (center) by using DSQOs. The proposed nonlinear model of DSQOs will be compared with the linear model of DeGroot and the nonlinear model of QSOs. Furthermore, we will show that the convergence of DSQOs is superior than DeGroot linear model and low-complex than QSOs nonlinear model.

Item Type: Conference or Workshop Item (Plenary Papers)
Additional Information: 6846/51909
Uncontrolled Keywords: consensus problem; convergence; doubly stochastic quadratic operators; multi-agent systems
Subjects: T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Information and Communication Technology
Kulliyyah of Information and Communication Technology
Depositing User: Dr. Sherzod Turaev
Date Deposited: 06 Oct 2016 15:50
Last Modified: 03 Oct 2019 09:18
URI: http://irep.iium.edu.my/id/eprint/51909

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year