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Nonlinear H2/H-Infinity Constrained Feedback Control A Practical Design Approach Using Neural Networks /

Modern aerospace, automotive, nautical, industrial, microsystem-assembly and robotic systems are becoming more and more complex. High-performance vehicles no longer have built-in error safety margins, but are inherently unstable by design to allow for more flexible maneuvering options. With the push...

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Detalles Bibliográficos
Main Authors: Abu-Khalaf, Murad. (Author, http://id.loc.gov/vocabulary/relators/aut), Huang, Jie. (http://id.loc.gov/vocabulary/relators/aut), Lewis, Frank L. (http://id.loc.gov/vocabulary/relators/aut)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:English
Publicado: London : Springer London : Imprint: Springer, 2006.
Edición:1st ed. 2006.
Series:Advances in Industrial Control,
Subjects:
Control engineering.
Electrical engineering.
Automotive engineering.
Industrial engineering.
Production engineering.
Artificial intelligence.
Chemical engineering.
Control and Systems Theory.
Electrical Engineering.
Automotive Engineering.
Industrial and Production Engineering.
Artificial Intelligence.
Industrial Chemistry/Chemical Engineering.
Acceso en liña:https://doi.org/10.1007/1-84628-350-7
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Table of Contents:
  • Preliminaries and Introduction
  • Policy Iterations and Nonlinear H 2 Constrained State Feedback Control
  • Nearly H 2 Optimal Neural Network Control for Constrained-Input Systems
  • Policy Iterations and Nonlinear H ? Constrained State Feedback Control
  • Nearly H ? Optimal Neural Network Control for Constrained-Input Systems
  • Taylor Series Approach to Solving HJI Equation
  • An Algorithm to Solve Discrete HJI Equations Arising from Discrete Nonlinear H ? Control Problems
  • H ? Static Output Feedback.

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