Optimization of Type-2 Fuzzy Controllers Using the Bee Colony Algorithm: SpringerBriefs in Applied Sciences and Technology
Autor Leticia Amador, Oscar Castilloen Limba Engleză Paperback – 5 mai 2017
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Specificații
ISBN-13: 9783319542942
ISBN-10: 331954294X
Pagini: 71
Ilustrații: VIII, 71 p. 40 illus., 31 illus. in color.
Dimensiuni: 155 x 235 x 4 mm
Greutate: 0.12 kg
Ediția:1st ed. 2017
Editura: Springer International Publishing
Colecția Springer
Seriile SpringerBriefs in Applied Sciences and Technology, SpringerBriefs in Computational Intelligence
Locul publicării:Cham, Switzerland
ISBN-10: 331954294X
Pagini: 71
Ilustrații: VIII, 71 p. 40 illus., 31 illus. in color.
Dimensiuni: 155 x 235 x 4 mm
Greutate: 0.12 kg
Ediția:1st ed. 2017
Editura: Springer International Publishing
Colecția Springer
Seriile SpringerBriefs in Applied Sciences and Technology, SpringerBriefs in Computational Intelligence
Locul publicării:Cham, Switzerland
Cuprins
Introduction.- Theory and Background.- Problems Statement.- Bee Colony Optimization Algorithm.-Simulation results for the Proposed Methods.- Statistical Analysis and Comparison of Results.- Conclusions.
Textul de pe ultima copertă
This book focuses on the fields of fuzzy logic, bio-inspired algorithm; especially bee colony optimization algorithm and also considering the fuzzy control area. The main idea is that this areas together can to solve various control problems and to find better results. In this book we test the proposed method using two benchmark problems; the problem for filling a water tank and the problem for controlling the trajectory in an autonomous mobile robot. When Interval Type-2 Fuzzy Logic System is implemented to model the behavior of systems, the results show a better stabilization, because the analysis of uncertainty is better. For this reason we consider in this book the proposed method using fuzzy systems, fuzzy controllers, and bee colony optimization algorithm improve the behavior of the complex control problems.
Caracteristici
Focuses on the fields of fuzzy logic, bio-inspired algorithm; especially bee colony optimization algorithm Serves as reference for scientists and engineers interested in applying fuzzy logic techniques for solving problems in intelligent control Presents recent research Includes supplementary material: sn.pub/extras