Sliding-Mode Fuzzy Neural Network-Based Voltage Controller for LC-Filtered CVCF Inverter System in Distributed Generation Units

This paper presents a sliding mode fuzzy neural network (SMFNN)-based voltage controller for a three-phase inductor and capacitor (LC)-filtered constant voltage constant frequency (CVCF) inverter system. The proposed controller integrates sliding mode control (SMC) for robustness against disturbances, fuzzy logic for adaptive tuning, and neural networks for self-learning and optimization. This hybrid controller effectively enhances performance under dynamic conditions by mitigating voltage fluctuations and ensuring precise regulation despite uncertainties in load variations and renewable energy sources. Comparative simulations demonstrate that the SMFNN-based controller outperforms conventional PI controllers in terms of voltage tracking accuracy and lower total harmonic distortion. The results confirm the efficacy of the proposed voltage controller in enhancing power quality and stability when embedding it in standalone distributed generation unit.