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In this article, a hybrid asynchronous particle swarm optimization-genetic algorithm (APSO-GA) is proposed for the removal of unwanted lower order harmonics in the cascaded H-bridge multilevel inverter (MLI). The APSO-GA is applicable to all levels of MLI. In the proposed method, ring topology based APSO is hybrid with GA. APSO is applied for exploration and GA is used for the exploitation of the best solutions. In this article, optimized switching angles are calculated using APSO-GA for seven-level and nine-level inverter, and results are compared with GA, PSO, APSO, bee algorithm (BA), differential evolution (DE), synchronous PSO, and teaching–learning-based optimization (TLBO). Simulation results show that APSO-GA can easily find feasible solutions particularly when the number of switching angles is high; however, the rest of all stuck at local minima due to less exploration capability. Also, the APSO-GA is less computational complex than GA, BA, TLBO, and DE algorithms. Experimentally, the performance of APSO-GA is validated on a single-phase seven-level inverter. [ABSTRACT FROM AUTHOR]

This study presents selective harmonic elimination pulse width modulation technique-based hybrid asynchronous PSO-Newton-Raphson (APSO-NR) algorithm for the elimination of undesired harmonics in cascaded H-bridge multilevel inverter. The proposed algorithm is applicable to all levels of MLI having equal and non-equal DC sources. In the proposed method, ring topology-based APSO algorithm is hybrid with NR method. APSO worked as a global search technique and NR is used for the refinement of best solutions. APSO-NR is applied to the seven-level inverter to eliminate fifth and seventh harmonics. In simulations, the performance of the proposed algorithm is compared with genetic algorithm, bee algorithm and particle swarm optimisation. The results proved that the proposed algorithm is efficient, and gives more precise firing angles in less number of iterations with high capability of tackling local optima. For the 48% of modulation index range, APSO-NR minimised the fitness function value lower than (10-25). The proposed algorithm is validated through the experimental implementation of the three-phase seven-level inverter. [ABSTRACT FROM AUTHOR]