ion Using Artificial Neu

System identification is one of the that needed to be considered before the con main objective of system identification is to kn system. It is essential to understand the proce it. Then we can go for controller design wh system. A number of methods are exi identification. In this paper we propose a met system model. The proposed method invo propagation neural network to predict the ou for a given input from the knowledge of past The effectiveness of the model identificatio experimental data from pressure process sta station, and conical tank process. e important aspects ntroller design. The ow the model of the ess before handling hich is apt for the isting for system thod to identify the olves use of back utput of the system t inputs & outputs. on is tested using ation, level process