A Dynamic Fuzzy Consensus Model with Random Iterative Steps

This paper presents a new dynamic model for fuzzy consensus that uses randomness in the modeling of the individual process iterations, this leads to singular (different) consensus process paths. The imprecision of the resulting different consensus results is captured by a simple process to form an overall consensus result from the distribution of the singular consensus results. The introduction of a random term into the dynamic process captures better the nature of real world consensus reaching processes. Using a random term in fuzzy consensus models in the way presented is a new contribution and presented here for the first time. The new model is illustrated with three numerical experiments.