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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems Design, Analysis and Matlab Simulation /

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the concrete design metho...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Liu, Jinkun (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Edición:1st ed. 2013.
Temas:
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Introduction
  • RBF Neural Network Design and Simulation
  • RBF Neural Network Control Based on Gradient Descent Algorithm
  • Adaptive RBF Neural Network Control
  • Neural Network Sliding Mode Control
  • Adaptive RBF Control Based on Global Approximation
  • Adaptive Robust RBF Control Based on Local Approximation
  • Backstepping Control with RBF
  • Digital RBF Neural Network Control
  • Discrete Neural Network Control
  • Adaptive RBF Observer Design and Sliding Mode Control.