Title :
Adaptive Inverse Control for Water Level of Boiler Drum Based on Neural Network
Author :
Peng, Daogang ; Zhang, Hao ; Yang, Ping ; Wang, Yong ; Xu, Chumei
Author_Institution :
Dept. of Inf. & Control Technol., Shanghai Univ. of Electr. Power
Abstract :
In order to control the water level in power plant, an adaptive inverse control based on neural network is presented in this paper. It adopted the steam flux signal to the inverse controller considering the influence of load changing, which has feed-forward compensation for steam flux disturbance and can avoid "false water level" phenomenon. At the same time, the whole input signals of controlled object are combined by a neural network inverse controller NNIC and a robust controller RC, which make up of a changing robust controller to control the object. Thus, good regulating performance is guaranteed in the initial control stage, even the controlled object varies later. Simulation results show that this strategy is effective and practicable
Keywords :
adaptive control; boilers; compensation; feedforward; level control; neurocontrollers; robust control; steam power stations; adaptive inverse control; boiler drum; feedforward compensation; inverse controller NNIC; neural network; power plant; robust controller RC; steam flux signal; water level control; Adaptive control; Boilers; Computer integrated manufacturing; Electronic mail; Feedforward systems; Neural networks; Power generation; Programmable control; Radio control; Robust control; adaptive inverse control; feed-forward compensation; neural network; water level control;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1712898