An Adaptive Quadrant Filter-based PLL Approach for a Three-Phase System with Adoptive Neuro-Fuzzy Interface System (ANFIS)
Keywords:
Phase-Locked-Loop (PLL), Synchronous Reference Frame, Adaptive Quadrature Filter Harmonic Distortion, Unbalanced Components, Adoptive Neuro-Fuzzy Interface System (ANFIS).Abstract
In recent Grid synchronization of electricity systems is required for Phase-Locked Loop (PLL) technologies, particularly when connecting renewable energy and improving power quality. Traditional Proportional-Integral (PI) controllers tend to face challenges in dynamic grid conditions, leading to slow responses and phase tracking instability. The work introduces an Adaptive Quadrant Filter-based Using a Synchronous Reference Frame Phase-Locked Loop (AQF-SRF-PLL) combined with an Adaptive Neuro-Fuzzy Inference System (ANFIS) controller, enhance tracking accuracy and robustness. The proposed approach employs the adaptive learning characteristics of ANFIS to adapt to grid variations, ensuring fast convergence, smaller steady-state error, and robustness against disturbance such as voltage sags and harmonics. Comparative simulations show that the ANFIS-based PLL outperforms the conventional PI-based PLL in terms of reaction time, stability of phase synchronization, and system longevity as a whole, and hence is a better solution for modern grid applications. The Matlab /Simulink simulation model is built, & the results. The simulations are presented to ensure that the mathematical analysis is correct.
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