Paper Info
Title
A Feasible Genetic Optimization Strategy for Parametric Interval Type-2 Fuzzy Logic Systems.
Abstract
This paper presents an optimization strategy for interval type-2 fuzzy systems by using the conjunction operation called the (p)-monotone sum of t-norms. A direct-current servomotor control system is implemented to test the performance of the type-1, interval type-2 and interval type-2 fuzzy systems with parametric operations, under several noisy conditions. To rate them, a multi-objective fitness function, based on the main transient parameters, is proposed to ensure the genetic algorithm to find the best squared feedback signal, when a white noise signal with different amplitudes is added to the reference. In addition, the optimization strategy includes the parametric conjunction suppression to analyze how a rule-associated parametric conjunction directly influences on system performance. Such rule suppression can be used to reduce the number of parametric conjunction operations required to obtain an additional performance improvement. Experimental results of the servomotor control system show that parametric conjunctions used in the interval type-2 fuzzy logic system provide additional advantages over its nonparametric counterpart.
Year
DOI
Venue
2018
10.1007/s40815-017-0307-0
Int. J. Fuzzy Syst.
Keywords
Field
DocType
Parametric interval type-2 fuzzy logic system optimization, Multi-objective transient fitness function, Genetic algorithms, Monotone sum, DC servomotor
Mathematical optimization,Control theory,Fitness function,White noise,Nonparametric statistics,Parametric statistics,Control system,Fuzzy control system,Mathematics,Genetic algorithm,Servomotor
Journal
Volume
Issue
ISSN
20
1
2199-3211
Citations 
PageRank 
References 
2
0.36
19
Authors
7
Name
Order
Citations
PageRank
Arturo Téllez-Velázquez120.36
Herón Molina-Lozano2124.77
Luis A. Villa3152.32
Raúl Cruz-Barbosa45511.02
Esther Lugo-González520.36
Ildar Batyrshin6328.63
Imre J. Rudas738863.89