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Optimization of Type-2 Fuzzy Controllers Using the Bee Colony Algorithm

  1. Údaje o názvuOptimization of Type-2 Fuzzy Controllers Using the Bee Colony Algorithm [electronic resource] / by Leticia Amador, Oscar Castillo.
    NakladatelCham : Springer International Publishing : Imprint: Springer, 2017.
    Fyz.popisVIII, 71 p. 40 illus., 31 illus. in color. online resource.
    ISBN9783319542959
    EdiceSpringerBriefs in Applied Sciences and Technology, ISSN 2191-530X
    Úplný obsahIntroduction -- Theory and Background -- Problems Statement -- Bee Colony Optimization Algorithm.-Simulation results for the Proposed Methods -- Statistical Analysis and Comparison of Results -- Conclusions.
    Poznámky k dostupnostiPřístup pouze pro oprávněné uživatele
    Dal.odpovědnost Castillo, Oscar.
    Dal.odpovědnost SpringerLink (Online service)
    Předmět.hesla Engineering. * Artificial intelligence. * Algorithms. * Calculus of variations. * Computational intelligence. * Control engineering. * Robotics. * Mechatronics.
    Forma, žánr elektronické knihy electronic books
    Země vyd.Německo
    Jazyk dok.angličtina
    Druh dok.Elektronické knihy
    URLPlný text pro studenty a zaměstnance UPOL
    kniha

    kniha


    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.

    Introduction -- Theory and Background -- Problems Statement -- Bee Colony Optimization Algorithm.-Simulation results for the Proposed Methods -- Statistical Analysis and Comparison of Results -- Conclusions.

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