Adaptive Inverse Control for Water Level of Boiler Drum Based on Neural Network

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