Title :
Automated generation of models for inferential control
Author_Institution :
Pavilion Technol., Austin, TX, USA
Abstract :
Over the past few years, we have implemented many models for inferential control. These models have been developed from historical data using statistical regression or neural network models. In addition, techniques for online biasing and robust model implementations have been developed. The methodology has been encapsulated in a novel software program. This software allows easy creation of models for inferential control
Keywords :
inference mechanisms; neural nets; parameter estimation; process control; real-time systems; statistical analysis; automated model generation; inferential control; neural network models; online biasing; parameter estimation; process control; statistical regression; Application software; Automatic control; Automatic generation control; Computer industry; Frequency; Industrial control; Neural networks; Predictive models; Robustness; Sampling methods;
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.1999.782339
