Real-time Selective Harmonic Minimization in unequal DC Source Inverters with PSO and RBFNN

In this paper a RBF neural network base harmonic elimination in multilevel inverters supplied from unequal dc sources is presented. This method uses PSO algorithm to obtain switching angles offline for different DC source values and then BRF neural network is trained to determine the optimum switching angles online. The variation of the dc sources affects the values of the switching angles required for each specific harmonic profile, as well as increases the difficulty of the harmonic elimination’s equations. Simulation results show the good performance of presented approach. As opposed to previous research in this area, the DC sources feeding the multilevel inverter are considered to be varying in time and selective harmonic eliminating is done. This implies that each one of the DC sources of this topology can have different values at any time but the output fundamental voltage will stay constant and the harmonic will still meet the specifications.

کلیدواژه ها:

Multilevel inverter ، selective harmonic elimination (SHE) ، PSO ، RBFNN