Fuzzy Sets in Dynamic Adaptation of Parameters of a Bee Colony Optimization for Controlling the Trajectory of an Autonomous Mobile Robot.
A hybrid approach composed by different types of fuzzy systems, such as the Type-1 Fuzzy Logic System (T1FLS), Interval Type-2 Fuzzy Logic System (IT2FLS) and Generalized Type-2 Fuzzy Logic System (GT2FLS) for the dynamic adaptation of the alpha and beta parameters of a Bee Colony Optimization (BCO) algorithm is presented. The objective of the work is to focus on the BCO technique to find the optimal distribution of the membership functions in the design of fuzzy controllers. We use BCO specifically for tuning membership functions of the fuzzy controller for trajectory stability in an autonomous mobile robot. We add two types of perturbations in the model for the Generalized Type-2 Fuzzy Logic System to better analyze its behavior under uncertainty and this shows better results when compared to the original BCO. We implemented various performance indices; ITAE, IAE, ISE, ITSE, RMSE and MSE to measure the performance of the controller. The experimental results show better performances using GT2FLS then by IT2FLS and T1FLS in the dynamic adaptation the parameters for the BCO algorithm.
Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana 22414, Mexico. leticia.amadorangulo@yahoo.com.mx.
Leticia
L
Amador-Angulo
Universidad Autónoma de Baja California, Tijuana 22390, Mexico. omendoza@uabc.edu.mx.
Olivia
O
Mendoza
Universidad Autónoma de Baja California, Tijuana 22390, Mexico. jrcastror@uabc.edu.mx.
Juan R
JR
Castro
Universidad Autónoma de Baja California, Tijuana 22390, Mexico. ardiaz@uabc.edu.mx.
Antonio
A
Rodríguez-Díaz
Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana 22414, Mexico. melin@tectijuana.edu.mx.
Patricia
P
Melin
Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana 22414, Mexico. ocastillo@tectijuana.mx.
Oscar
O
Castillo
autonomous mobile robot; bee colony optimization; dynamic adaptation; fuzzy controller; fuzzy sets; membership functions; perturbation; uncertainty