A Generalized Type-2 Fuzzy Logic System for the dynamic adaptation the parameters in a Bee Colony Optimization algorithm applied in an autonomous mobile robot control

Abstract

A hybrid system composed by a generalized Type-2 Fuzzy Logic System (GT2FLS) and a fuzzy Bee Colony Optimization (FBCO) algorithm for the dynamic adaptation in the alpha and beta parameters is presented in this paper. The Bee Colony Optimization meta-heuristic belongs to the class of Nature-Inspired Algorithms. The objective of the work is the analysis of the approach with Generalized Type-2 Fuzzy Logic System to find the best beta and alpha parameter values in BCO. We use BCO specifically for tuning the membership functions of the fuzzy controller for trajectory stability in a mobile robot. We implemented IAE, ISE, RMSE and MSE, which are performance indices to measure the controller behavior. We add perturbations in the model with the pulse generator for the Generalized Type-2 Fuzzy Logic System and analyze better the uncertainty and that the FBCO shows better results than the original BCO.