Abstract

A bstract In this paper, a new control method for adaptive selective harmonic elimination in a quasi Z-source cascaded multilevel inverter (QZS-CMI) is proposed. A ccording to real condition , the DC sources feeding the inverter are considered to be varying in time. In th is condition, the switching angle and shoot-through duty ratio for each module are obtained off - line for different DC source values using particle swarm optimization (PSO) algorithm. The off-line data set which is obtained by the PSO algorithm is used for training an artificial neural network (ANN). Finally, this ANN is used for determining the switching angle and shoot-through duty ratio for each module corresponding to the real-time values of DC sources. In the proposed method , although each one of the DC sources can have different values according to real condition, the fundamental component of the output voltage will stay constant and the harmonic content will still meet the desired specifications . The effectiveness of the proposed method was shown by simulation in PSCAD/EMTDC software . Keywords : Quasi Z-source cascaded multilevel inverter, Selective harmonic elimination, Particle swarm optimization, Artificial neural network

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