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

• Κύριοι συγγραφείς: Sanchez, Edgar N. (Συγγραφέας), Alanís, Alma Y. (Συγγραφέας), Loukianov, Alexander G. (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.
• Σειρά: Studies in Computational Intelligence, 112
• Θέματα: Engineering.; Artificial intelligence.; System theory.; Statistical physics.; Dynamical systems.; Applied mathematics.; Engineering mathematics.; Control engineering.; Robotics.; Mechatronics.; Appl.Mathematics/Computational Methods of Engineering.; Artificial Intelligence (incl. Robotics).; Statistical Physics, Dynamical Systems and Complexity.; Control, Robotics, Mechatronics.; Systems Theory, Control.

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...

Πίνακας περιεχομένων:

• 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.