Internal model control using GA-NN for boiler drum

The water level system of boiler drum is a multi-disturbance complicated process. An internal model control using GA-NN for the water level system of boiler drum of the power plant is presented in this paper. The neural model of the system is identified as an estimator. Another neural network is trained to learn the inverse dynamics of the system so that it can be used as a nonlinear controller. Because of the limitation of BP algorithm, the genetic algorithm is used to find the fitness weights and thresholds of the neural network model, and the simulation results testify that the model is satisfied and the control is effective.