DocumentCode :
835509
Title :
Introduction to neural networks for intelligent control
Author :
Bavarian, Behnam
Author_Institution :
Robotics Res. Lab., California Univ., Irvine, CA, USA
Volume :
8
Issue :
2
fYear :
1988
fDate :
4/1/1988 12:00:00 AM
Firstpage :
3
Lastpage :
7
Abstract :
Neural network architecture is presented as one approach to the design and implementation of intelligent control systems. Neural networks can be considered as massively parallel distributed processing systems with the potential for ever-improving performance through dynamical learning. The nomenclature and characteristics of neural networks are outlined. Two simple examples are presented to illustrate applications to control systems: one is fault isolation mapping, and the other involves optimization of a Hopfield network that defines a clockless analog-to-digital conversion.<>
Keywords :
computer architecture; control system synthesis; learning systems; neural nets; parallel processing; Hopfield network; clockless analog-to-digital conversion; control design; dynamical learning; fault isolation mapping; intelligent control; intelligent control systems; massively parallel distributed processing systems; neural network architecture; optimization; Adaptive control; Control systems; Distributed processing; Feedback control; Feedback loop; Intelligent control; Neural networks; Robust control; Sensor systems; Uncertainty;
fLanguage :
English
Journal_Title :
Control Systems Magazine, IEEE
Publisher :
ieee
ISSN :
0272-1708
Type :
jour
DOI :
10.1109/37.1866
Filename :
1866
Link To Document :
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