Title :
Adaptive Neural Network Control for Drum Water Level Based on Fuzzy Self-Tuning
Author :
Han, Pu ; Mao, Xin-jing ; Jiao, Song-ming ; Sun, Hai-rong ; Zhou, Li-hui
Author_Institution :
Dept. of Autom., North China Electr. Power Univ., Baoding
Abstract :
An adaptive neural network control strategy based on fuzzy self-tuning is presented. The strategy is applied to the control system for drum water level of coal-fired power plant. Fuzzy inference engine (FIE) is used to train neural network online. The control strategy possesses feedforward compensation ability for steam flow disturbance by introducing the steam flow signal to neural network controller. Robust controller is constructed to guarantee good regulating performance while dynamic behavior of the controlled plant changes or external steam flow disturbance exists. In contrast to conventional cascade PID control, simulation results show efficiency and superiority of the proposed strategy
Keywords :
adaptive control; coal; compensation; feedforward; fuzzy control; fuzzy reasoning; learning (artificial intelligence); level control; neurocontrollers; power generation control; power plants; self-adjusting systems; steam power stations; adaptive neural network control; coal-fired power plant; drum water level control system; feedforward compensation ability; fuzzy inference engine; fuzzy self-tuning; online neural network training; robust controller design; steam flow disturbance; Adaptive control; Adaptive systems; Control systems; Engines; Feedforward neural networks; Fuzzy control; Fuzzy neural networks; Neural networks; Power generation; Programmable control; Adaptive control; Drum water level feedforward compensation; Neural networks;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.259030