Nuclear steam generator level control by a neural network-tuning 2-DOF PID controller

This paper focuses on the level control of a steam generator in a nuclear power plant. It is very difficult to effectively control the level of the nuclear steam generator, because of the swelling and shrinking caused by many kinds of disturbances, such as feed water rate, feed water temperature, main steam flow rate, and coolant temperature. Up to the present time, the PI controller has been used for the level control, owing to the easy control algorithms and the advantage which have been proven on the nuclear power plant. However, since there are problems with stability control during low power and start-up, only a highly experienced operator can operate during those procedures. A great deal of time and an expensive simulator is needed for the training of an operator. In addition to studying this problem, this paper has studied the tuning of a 2-DOF PID (two-degrees of freedom PID) controller by a neural network in the level control of the steam generator of a nuclear power plant, through the simulation and the experimentation of the model steam generator. Results obtained by simulation reveal the importance of the controller tuning in nuclear steam generator level control, and results obtained on the experimental steam generator suggest methods which can be used to reduce swelling and shrinking.