Iterative Learning Control Robustness and Monotonic Convergence for Interval Systems /

This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. Two key problems with the fundamentals of iterative learning control (ILC) design as treated by existing work are: first, many ILC design strategies assume nominal knowledg...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Ahn, Hyo-Sung (Autor), Moore, Kevin L. (Autor), Chen, YangQuan (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Springer London : Imprint: Springer, 2007.
Edición:1st ed. 2007.
Colección:Communications and Control Engineering,
Temas:
Control engineering.
System theory.
Control theory.
Artificial intelligence.
Robotics.
Automation.
Bioinformatics.
Biomedical engineering.
Control and Systems Theory.
Systems Theory, Control .
Artificial Intelligence.
Control, Robotics, Automation.
Biomedical Engineering and Bioengineering.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Iterative Learning Control Overview
  • An Overview of the ILC Literature
  • The Super-vector Approach
  • Robust Interval Iterative Learning Control
  • Robust Interval Iterative Learning Control: Analysis
  • Schur Stability Radius of Interval Iterative Learning Control
  • Iterative Learning Control Design Based on Interval Model Conversion
  • Iteration-domain Robustness
  • Robust Iterative Learning Control: H? Approach
  • Robust Iterative Learning Control: Stochastic Approaches
  • Conclusions.

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