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Sensors 2016, 16(9), 1458; doi:10.3390/s16091458

Fuzzy Sets in Dynamic Adaptation of Parameters of a Bee Colony Optimization for Controlling the Trajectory of an Autonomous Mobile Robot

1
Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana 22414, Mexico
2
Universidad Autónoma de Baja California, Tijuana 22390, Mexico
*
Author to whom correspondence should be addressed.
Academic Editor: Dan Zhang
Received: 28 May 2016 / Revised: 24 August 2016 / Accepted: 29 August 2016 / Published: 9 September 2016
(This article belongs to the Special Issue Advanced Robotics and Mechatronics Devices)

Abstract

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. View Full-Text
Keywords: bee colony optimization; fuzzy controller; fuzzy sets; uncertainty; dynamic adaptation; membership functions; perturbation; autonomous mobile robot bee colony optimization; fuzzy controller; fuzzy sets; uncertainty; dynamic adaptation; membership functions; perturbation; autonomous mobile robot
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Amador-Angulo, L.; Mendoza, O.; Castro, J.R.; Rodríguez-Díaz, A.; Melin, P.; Castillo, O. Fuzzy Sets in Dynamic Adaptation of Parameters of a Bee Colony Optimization for Controlling the Trajectory of an Autonomous Mobile Robot. Sensors 2016, 16, 1458.

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