An Enhanced Repetitive Control Framework for Adaptive Neuro-Fuzzy Learning Grid-Connected Inverter with Current Control and Frequency Adaptability

This work proposes an advanced repeated control method (RCM) for a frequency adaptable grid-connected inverter based on fuzzy current control. The primary goal of the suggested strategy is to lower total harmonic distortion (THD) by adjusting the FIR filter in accordance with shifting grid frequencies while maintaining resonant frequencies that match both the fundamental and harmonic grid frequencies. When it is necessary that the sampling frequency ratio be an integer, the repeated control system is chosen due to its high efficiency in tracking periodic signals and low output total harmonic distortion (THD). The RCM’s resonant frequencies will deviate from the actual grid’s fundamental and harmonic frequencies in an industrial setting where the ratio may not be an integer. As a result, the system’s performance may be negatively impacted. against determine whether the suggested control method improves performance, it is compared against a conventional repeated control strategy that uses a PI controller. Through trials conducted at various frequencies, the control approach is assessed in grid-connected mode. The suggested controller successfully demonstrates its superiority over alternative control schemes with regard to the inverter systems’ THD level and component harmonic.