DocumentCode
343194
Title
Neural-network control in the metals industry
Author
Wilson, Edward
Author_Institution
SAI Int., Redwood Shores, CA, USA
Volume
3
fYear
1999
fDate
1999
Firstpage
1657
Abstract
Because of their capabilities for adaptation, nonlinear function approximation, and parallel hardware implementation neural networks have proven to be well suited for some important control applications. The paper briefly presents three examples of neural-network control applications on laboratory and industrial hardware. An overall problem-solving approach is presented as well as suggestions for neural-network research that will benefit industrial control optimization
Keywords
function approximation; gradient methods; learning (artificial intelligence); metallurgical industries; neurocontrollers; process control; industrial control optimization; industrial hardware; laboratory hardware; metals industry; neural-network control; problem-solving approach; Adaptive control; Control systems; Intelligent networks; Metals industry; Neural networks; Nonlinear control systems; Orbital robotics; Predictive control; Programmable control; Space technology;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 1999. Proceedings of the 1999
Conference_Location
San Diego, CA
ISSN
0743-1619
Print_ISBN
0-7803-4990-3
Type
conf
DOI
10.1109/ACC.1999.786110
Filename
786110
Link To Document