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Herausgeber: 
  • Uzay Kaymak
  • Joao M Costa Sousa
  • Fuzzy Decision Making In Modeling And Control 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Dezember 2002  
    Genre:  EDV / Informatik 
    ISBN:  9789810248772 
    EAN-Code: 
    9789810248772 
    Verlag:  World Scientific Publishing Company 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  World Scientific Series In Robotics And Intelligent Systems  
    Dimensionen:  H 236 mm / B 162 mm / D 23 mm 
    Gewicht:  621 gr 
    Seiten:  356 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Decision making and control are two fields with distinct methods for solving problems, and yet they are closely related. This book bridges the gap between decision making and control in the field of fuzzy decisions and fuzzy control, and discusses various ways in which fuzzy decision making methods can be applied to systems modeling and control.Fuzzy decision making is a powerful paradigm for dealing with human expert knowledge when one is designing fuzzy model-based controllers. The combination of fuzzy decision making and fuzzy control in this book can lead to novel control schemes that improve the existing controllers in various ways. The following applications of fuzzy decision making methods for designing control systems are considered: - Fuzzy decision making for enhancing fuzzy modeling. The values of important parameters in fuzzy modeling algorithms are selected by using fuzzy decision making.- Fuzzy decision making for designing signal-based fuzzy controllers. The controller mappings and the defuzzification steps can be obtained by decision making methods.- Fuzzy design and performance specifications in model-based control. Fuzzy constraints and fuzzy goals are used.- Design of model-based controllers combined with fuzzy decision modules. Human operator experience is incorporated for the performance specification in model-based control.The advantages of bringing together fuzzy control and fuzzy decision making are shown with multiple examples from real and simulated control systems.

      



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