System Identification of a Nonlinear Multivariable Steam Generator Power Plant Using Time Delay and Wavelet Neural Networks

One of the most effective strategies for steam generator efficiency enhancement is to improve the control system. For such an improvement، it is essential to have an accurate model for the steam generator of power plant. In this paper، an industrial steam generator is considered as a nonlinear multivariable system for identification. An important step in nonlinear system identification is the development of a nonlinear model. In recent years، artificial neural networks have been successfully used for identification of nonlinear systems in many researches. Wavelet neural networks (WNNs) also are used as a powerful tool for nonlinear system identification. In this paper we present a time delay neural network model and a WNN model in order to identify an industrial steam generator. Simulation results show the effectiveness of the proposed models in the system identification and demonstrate that the WNN model is more precise to estimate the plant outputs.