Title :
Neural-network control in the metals industry
Author_Institution :
SAI Int., Redwood Shores, CA, USA
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;
Conference_Titel :
American Control Conference, 1999. Proceedings of the 1999
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4990-3
DOI :
10.1109/ACC.1999.786110
