Adaptive Neural Network Control for Drum Water Level Based on Fuzzy Self-Tuning

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.