Karim, Siti Nurlaili and Roslan, Nur Syahirah and Abdullah Sani, Sarah A’fifah and Che Lah, Nur Syadhila and Hamzah, Nur Zatul Akmar (2026) Consensus convergence of multi-agent systems controlled via geometric quadratic stochastic operators. In: International Conference on Mathematical Sciences and Technology 2024, MathTech 2024, 3 December 2024 - 5 December 2024, Penang.
|
PDF
- Published Version
Download (312kB) | Preview |
|
|
PDF (Scopus)
- Supplemental Material
Download (194kB) | Preview |
Abstract
Consensus control in multi-agent systems has emerged as a key domain of research, owing to its broad implementations in numerous fields. However, achieving consensus, where all agents agree on a common value, presents a key challenge in the study of multi-agent coordination. To address this, consensus models are formulated and developed specifically to solve such problems. Previous empirical and theoretical studies have shown that nonlinear models outperform linear models in tackling consensus challenges. Limited studies of the nonlinear consensus models promote the idea of a potential nonlinear model utilising Geometric quadratic stochastic operators (QSOs). This paper proposed Geometric QSOs for solving consensus problems in the systems of multi-agent. For consensus convergence, the suggested method makes advantage of a nonlinear class of family of QSOs with geometric distribution. The foundation of the nonlinear protocols for Geometric QSOs is probability and measure theory. The study uses geometric QSOs to examine how the multi-agent systems converge to the ideal value. An investigation was conducted in comparison between the DeGroot model and current nonlinear models. Our results suggest that the suggested nonlinear consensus model can be used to solve a more sophisticated consensus problem.
| Item Type: | Proceeding Paper (UNSPECIFIED) |
|---|---|
| Uncontrolled Keywords: | consensus, convergence, nonlinear operator |
| Subjects: | Q Science > QA Mathematics > QA300 Analysis |
| Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Science Kulliyyah of Science > Department of Computational and Theoretical Sciences |
| Depositing User: | Nur Zatul Akmar Hamzah |
| Date Deposited: | 01 Aug 2026 11:27 |
| Last Update: | 01 Aug 2026 11:27 |
| Queue Number: | 2026-07-Q4390 |
| URI: | http://irep.iium.edu.my/id/eprint/130354 |
Actions (login required)
 |
View Item |