Development of a neural network based integrated control system of 120 ton/h capacity boiler
An integrated control system based on artificial neural network (ANN) is presented in this paper to control a 120 ton/h capacity boiler of the Zia Fertilizer Company Limited (ZFCL), Ashuganj, Bangladesh. The process inverse dynamic modelling technique is applied to design the proposed controller. A multilayer feed-forward neural network is trained to identify the unknown inverse dynamic model of the boiler plant by a well known learning algorithm called backpropagation. The training data were collected from the history file of ZFCL. A new software controller is then developed for integrated control system of the ZFCL boiler using the weights of the trained network. Both the training mode and running mode of the developed controller are presented in this paper. The controller output is also converted into electrical signal using pulse width control technique. The generated signal is used for on-line regulation of the control valve through the parallel port of the computer. The developed controller is tested by using the boiler inputoutput data that are not used during the training. The output response and performance of the developed controller is compared with those of the existing PID controller of the plant.
neural network integrated control boiler pid controller