Modelling of Nonlinear superheated temperature control process using neural networks

This Paper presents a Nonlinear models for the left and right super heater tubes of the superheated steam control process of thermal power plant using neural networks. The realtime data which is obtained by measuring the process variables at frequent intervals for one day is used to train a neural network. The network was validated and tested. The models developed faithfully duplicate the superheated steam temperature control process. These models can be used for the design of controller for super heated steam temperature control process.