L
Leticia Amador-Angulo
Publications - 24
Citations - 883
Leticia Amador-Angulo is an academic researcher. The author has contributed to research in topics: Fuzzy logic & Fuzzy control system. The author has an hindex of 11, co-authored 22 publications receiving 672 citations.
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A comparative study of type-1 fuzzy logic systems, interval type-2 fuzzy logic systems and generalized type-2 fuzzy logic systems in control problems
TL;DR: This paper presents a comparative study of type-2 fuzzy logic systems with respect to intervaltype-2 and type-1 fuzzy Logic systems to show the efficiency and performance of a generalized type- 2 fuzzy logic controller (GT2FLC) to design the fuzzy controllers of complex non-linear plants.
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A generalized type-2 fuzzy logic approach for dynamic parameter adaptation in bee colony optimization applied to fuzzy controller design
TL;DR: Simulation results illustrate that the implementation of the GT2FLS approach improves its performance when using the BCO algorithm and the stability of the fuzzy controller is better when compared with respect to a type-1 Fuzzy Logic Controller (T1FLC) and an Interval type-2 fuzzy logic Controller (IT2FLC).
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A new fuzzy bee colony optimization with dynamic adaptation of parameters using interval type-2 fuzzy logic for tuning fuzzy controllers
TL;DR: This paper considered different levels and types of noise in the simulations to analyze the approach of interval type-2 fuzzy logic systems to find the best values of alpha and beta for BCO when applied in the design of fuzzy controllers.
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Fuzzy Sets in Dynamic Adaptation of Parameters of a Bee Colony Optimization for Controlling the Trajectory of an Autonomous Mobile Robot
Leticia Amador-Angulo,Olivia Mendoza,Juan R. Castro,Antonio Rodríguez-Díaz,Patricia Melin,Oscar Castillo +5 more
TL;DR: This work uses BCO specifically for tuning membership functions of the fuzzy controller for trajectory stability in an autonomous mobile robot and adds two types of perturbations in the model for the Generalized Type-2 Fuzzy Logic System to better analyze its behavior under uncertainty.
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Comparative Study of Type-2 Fuzzy Particle Swarm, Bee Colony and Bat Algorithms in Optimization of Fuzzy Controllers
Frumen Olivas,Leticia Amador-Angulo,Jonathan Perez,Camilo Caraveo,Fevrier Valdez,Oscar Castillo +5 more
TL;DR: A comparison among Particle swarm optimization, Bee Colony Optimization and the Bat Algorithm is presented and simulation results reveal that PSO algorithm outperforms the results of the BCO and BA algorithms.