NeuroFuzzy Full-Recurrent Hybrid B-Spline Wavelet Based Feedback Linearization Control for PMSG-WECS in a Grid-connected Hybrid Power System

The research article presents a novel maximum power point tracking (MPPT) control scheme to extract maximum power from a grid-connected wind energy conversion system (WECS). The control scheme is based on adaptive feedback linearization embedded full-recurrent adaptive Neuro-Fuzzy hybrid B-Spline wavelet control (FBL-FRANF-HBs-WC). FRANF-HBs-WC architecture estimates the nonlinear functions of FBL using B-Spline membership function and the Morlet wavelet network in the antecedent and the consequent parts, respectively. The MPPT performance using FBL-FRANF-HBs-WC is validated for the permanent magnet synchronous generator (PMSG) based WECS through simulation testbed implemented in MATLAB/Simulink. The performance parameters are compared against adaptive PID (aPID) for varying wind speed and grid-connected load for 24 hours.