TY - JOUR
T1 - Consensus of fractional nonlinear dynamics stochastic operators for multi-agent systems
AU - Abdulghafor, Rawad
AU - Turaev, Sherzod
N1 - Funding Information:
We would like to thank Kulliyyah of Information and Communication Technology and the Research Management Center of the International Islamic University Malaysia (IIUM) for their support. This work is supported by the MOHE through IIUM Research Initiative Grant Scheme RIGS16-368-0532 .
Publisher Copyright:
© 2017 Elsevier B.V.
PY - 2018/11
Y1 - 2018/11
N2 - In this paper, we consider nonlinear models of DeGroot, quadratic stochastic operators (QSO) and doubly stochastic quadratic operators (DSQO) with fractional degree for consensus problem in multi-agent systems (MAS). By the limit behaviour of nonlinear approach, we discuss the convergence of the solutions of the models considered. The findings from the results of the carried out investigation demonstrates an efficient approach to convergence for consensus problem in MAS. The main advantages of the proposed work are i) fast convergence to consensus ii) flexible and low complexity in computation iii) ability to achieve optimal consensus. The study is built on fractional representation of [Formula presented] where n → ∞. Further, the simulation results on the related protocols are also presented.
AB - In this paper, we consider nonlinear models of DeGroot, quadratic stochastic operators (QSO) and doubly stochastic quadratic operators (DSQO) with fractional degree for consensus problem in multi-agent systems (MAS). By the limit behaviour of nonlinear approach, we discuss the convergence of the solutions of the models considered. The findings from the results of the carried out investigation demonstrates an efficient approach to convergence for consensus problem in MAS. The main advantages of the proposed work are i) fast convergence to consensus ii) flexible and low complexity in computation iii) ability to achieve optimal consensus. The study is built on fractional representation of [Formula presented] where n → ∞. Further, the simulation results on the related protocols are also presented.
KW - Consensus problem
KW - Fractional consensus
KW - Multi-agent systems
KW - Nonlinear stochastic operators
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U2 - 10.1016/j.inffus.2017.11.003
DO - 10.1016/j.inffus.2017.11.003
M3 - Article
AN - SCOPUS:85036475863
SN - 1566-2535
VL - 44
SP - 1
EP - 21
JO - Information Fusion
JF - Information Fusion
ER -