Title :
ANN control based on generalized minimum variance and its application to boiler-burning system
Author :
Cui, Baomin ; Liu, Hao ; Zhao, Hengbao
Author_Institution :
Dept. of Comput. & Syst. Sci., Nankai Univ., Tianjin, China
Abstract :
Generally, the training of artificial neural networks (ANNs) involved in a control system can be performed online depending on whether they execute useful work or not while learning is taking place. The aim of this paper is to apply a novel ANN self-tuning controller based on the generalized minimum variance controller and multiplayer neural network architecture to process control by online training the neural emulator and controller. Finally, we introduce the application of the controller to a boiler-burning system
Keywords :
boilers; feedforward neural nets; learning (artificial intelligence); neurocontrollers; nonlinear systems; process control; real-time systems; self-adjusting systems; boiler-burning system; generalized minimum variance; multiplayer neural networks; nonlinear systems; online learning; process control; self-tuning controller; Application software; Artificial neural networks; Biological control systems; Biological neural networks; Chemical technology; Control systems; Industrial control; Industrial training; Process control; Robust control;
Conference_Titel :
Industrial Technology, 1994., Proceedings of the IEEE International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
0-7803-1978-8
DOI :
10.1109/ICIT.1994.467188
