Research on the NNARX Model Identification of Hydroelectric Unit Based on Improved L-M Algorithm

Abstract

Its hard to use traditional ways to set up a hydroelectric power plant model due to its complex, time-varying and nonlinear characteristics. This article uses the neural network autoregressive with exogenous input (NNARX) to identify and model hydro-turbine generating unit which is the key in the hydroelectric power plant modeling. The random guide vain signal is used to train NNARX in this paper and the other two working conditions are used to check its generalization ability. In order to improve identification accuracy, generalization performance and training speeds, an improved Levenberg-Marquardt algorithm is proposed in this article which is based on the L-M algorithm that widely used in artificial neural network weights adjustment. Simulation results indicate that NNARX model with improved L-M algorithm can reach high recognition accuracy and have good generalization ability. It can provide a good simulation model for intelligent controller design in the future.