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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Detalhes bibliográficos
Principais autores: Abu-Khalaf, Murad. (Autor, 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: Recurso Eletrônico livro eletrônico
Idioma:English
Publicado em: London : Springer London : Imprint: Springer, 2006.
Edição:1st ed. 2006.
coleção:Advances in Industrial Control,
Assuntos:
Acesso em linha:https://doi.org/10.1007/1-84628-350-7
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Sumário:
  • 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.