A PLL control based on algorithm of BP neural network

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