A Method of Phase Tracking Based on Neural Network

For parallel operation of electric network it need to control the current to be in phase with the electric network voltage. This paper presents a control method of phase tracking based on artificial neural network. After comparing the simulation results between BP network and RBF network, it takes the algorithm of RBF network into phase locked loop. It takes the electric network voltage as the expected output and current as training sample. Then through the self-learning of neural network it can gradually reduce the error of output between the sample and the expected target, and achieve the the synchronization and tracking of the expected output. In this paper it has been carried out through digital dynamic simulation using the MATLAB simulink power system toolbox. The results of simulation shows that it can track its target well and have strong adaptive capacity.