Reach a nonlinear consensus for MAS via doubly stochastic quadratic operators - Abdulghafor, Rawad Abdulkhaleq Abdulmolla; Turaev, Sherzod; M.Khedher, Akram M. Zeki; Alshaikhli, Imad Fakhri Taha (Taylor & Francis, 2017)
This technical note addresses the new nonlinear protocol class of doubly stochastic quadratic operators (DSQOs) for coordination of consensus problem in multi-agent systems (MAS). We derive the conditions for ensuring that every agent reaches consensus on a desired rate of the group’s decision where the group decision value in its agent’s initial statuses varies. Besides that, we investigate a non-linear protocol sub-class of extreme DSQO (EDSQO) to reach a consensus for MAS to a common value with nonlinear low-complexity rules and fast time convergence if the interactions for each agent