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Autor(en): 
  • Kevin L. Moore
  • Iterative Learning Control for Deterministic Systems 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 5-10 Tagen versandfertig
    Veröffentlichung:  Dezember 2011  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Algorithms / artificialneuralnetwork / ArtificialNeuralNetworks / associativememory / backpropagation / Computer-Aided Design (CAD) / Control / controlsystem
    ISBN:  9781447119142 
    EAN-Code: 
    9781447119142 
    Verlag:  Springer 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D 10 mm 
    Gewicht:  271 gr 
    Seiten:  172 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    The material presented in this book addresses the analysis and design of learning control systems. It begins with an introduction to the concept of learning control, including a comprehensive literature review. The text follows with a complete and unifying analysis of the learning control problem for linear LTI systems using a system-theoretic approach which offers insight into the nature of the solution of the learning control problem. Additionally, several design methods are given for LTI learning control, incorporating a technique based on parameter estimation and a one-step learning control algorithm for finite-horizon problems. Further chapters focus upon learning control for deterministic nonlinear systems, and a time-varying learning controller is presented which can be applied to a class of nonlinear systems, including the models of typical robotic manipulators. The book concludes with the application of artificial neural networks to the learning control problem. Three specificways to neural nets for this purpose are discussed, including two methods which use backpropagation training and reinforcement learning. The appendices in the book are particularly useful because they serve as a tutorial on artificial neural networks.

      



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