Discrete-Time High Order Neural Control Trained with Kalman Filtering /

The objective of this work is to present recent advances in the theory of neural control for discrete-time nonlinear systems with multiple inputs and multiple outputs. The results that appear in each chapter include rigorous mathematical analyses, based on the Lyapunov approach, in order to guarante...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Sanchez, Edgar N. (Autor), Alanís, Alma Y. (Autor), Loukianov, Alexander G. (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2008.
Edición:1st ed. 2008.
Colección:Studies in Computational Intelligence,
Temas:
Engineering mathematics.
Engineering-Data processing.
Artificial intelligence.
System theory.
Control engineering.
Robotics.
Automation.
Control theory.
Mathematical physics.
Mathematical and Computational Engineering Applications.
Artificial Intelligence.
Complex Systems.
Control, Robotics, Automation.
Systems Theory, Control .
Theoretical, Mathematical and Computational Physics.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Mathematical Preliminaries
  • Discrete-Time Adaptive Neural Backstepping
  • Discrete-Time Block Control
  • Discrete-Time Neural Observers
  • Discrete-Time Output Trajectory Tracking
  • Real Time Implementation
  • Conclusions and Future Work.

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