Design and Performance Analysis of Phase Lock Loop using ANFIS under Non-Ideal Conditions

The following paper briefs about design and performance analysis of phase lock loop (PLL) of an inverter under non ideal grid conditions using adaptive network based fuzzy inference system (ANFIS) intelligent controller. The detection of phase angle is key in the grid. To maintain its accuracy of tracking phase angle, frequency, amplitude and quality of power, it is necessary to design an adaptive intelligent non-linear controller to handle the non-idealities in the grid. Fuzzy logic is used to modify the PI controller’s gains in order to quickly acquire the phase angle performance under different network fluctuations and disruptions. This article mainly deals with Synchronous reference frame phase lock loop (SRF-PLL) design with proportional integral (PI) controller, intelligent fuzzy logic controller and intelligent ANFIS controller for ideal and non-ideal grid conditions like phase jump, frequency variation etc. The developed system is tested in the MATLAB/Simulink and simulation results are compared to proportional-integral (PI) and intelligent fuzzy logic controllers for non-ideal grid conditions. Under non-ideal conditions, simulation tests revealed that the ANFIS-based controller outperformed the fuzzy and PI controllers in terms of accuracy.