Parameter Identification of Excitation Systems Based on Hopfield Neural Network

The parameter identification based on Hopfield neural network (HNN) was applied to a static excitation system. The applicable algorithm of the identification method was given in detail. Nine-parameter excitation system was studied. The HNN of twenty neurons were designed in order to identify these parameters. Finally model validation was performed. Numerical simulation results testify that this method has high precision and quick convergence. The method can be implemented with electronic circuit, so it will benefit the on-line parameter identification of the excitation system and will have significance to any system that can be described by state space model.