Elimination of Harmonics in Multilevel Inverter Using Multi-Group Marine Predator Algorithm-Based Enhanced RNN

Multilevel inverters (MLI) are becoming more common in different power applications, such as active filters, elective vehicle drives, and dc sources. The Multi-Group Marine Predator Algorithm (MGMPA) is introduced this study for resolving transcendental nonlinear equations utilizing an MLI a selective harmonic elimination (SHE) approach. Its applicability superiority over various SHE approaches utilized recent research may be attributed to its high accuracy, likelihood of convergence, improved output voltage quality. For the entire modulation index, optimum switching angles (SA) from (MPA) control three-phase 11-level employing cascaded H-bridge (CHB) architecture regulate vital element eliminate harmonics. limitation that it difficult find solutions equations. As result, specific optimization must used. Artificial Intelligence (AI) algorithms can handle equation successfully, although their time consumption well convergence abilities vary. Here, recurrent neural network (RNN) considered where hidden neurons tuned by MGMPA with intention distortion parameter (HDP) minimization, thus called enhanced (ERNN). method’s resilience consistency demonstrated simulation analytical findings. method effective appropriate than including MPA, Harris Hawks (HHO), Whale algorithm (WOA), according data.