A novel phase-locked loop based on Hopfield neural network optimum algorithm

This paper presents a new optimum design of phase-locked loop applying Hopfield neural network and its virtual realization based on LabVIEW. A novel quadrature phase-locked loop (QPLL) based on LabVIEW virtual implementation is introduced. Advantages of the proposed PLL over the conventional PLLs are its capability of providing the fundamental component of the input signal which is not only locked in phase but also in amplitude to the actual signal while providing an estimate of its frequency. Performance of the QPLL is immune to noise and distortions. It is capable of following large and abrupt variations of the frequency with a speed which is readily controllable. The experiment results show that the methods have the characteristics of real time, high precision and immunity with respect to noise and distortions.