Evolutionary Learning Algorithms for Neural Adaptive Control

phe05
ISBN: 978-3-540-76161-7
Verlag: Springer

Buch, Englisch, 211 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 347 g

Reihe: Perspectives in Neural Computing

Evolutionary Learning Algorithms for Neural Adaptive Control is an advanced textbook, which investigates how neural networks and genetic algorithms can be applied to difficult adaptive control problems which conventional results are either unable to solve, or for which they can not provide satisfactory results. It focuses on the principles involved, rather than on the modelling of the applications themselves, and therefore provides the reader with a good introduction to the fundamental issues involved.

Zielgruppe

Graduate

Autoren/Hrsg.

Dracopoulos, Dimitris C.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Fuzzy-Systeme
• Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Überwachungstechnik

Inhaltsverzeichnis

Introduction.- Dynamic systems and control.- The attitude control problem.- Artificial neural networks.- Neuromodels of dynamic systems.- Current neurocontrol techniques.- Genetic algorithms.- Adaptive control architectures.- Conclusions and the future.- A. Euler equations solutions.- B. An attitude control simulator.- Bibliography.- Index.