Neural Network Controller for Asymmetric Cascaded Multilevel Inverter

Abstract

Among the Artificial Intelligent (AI) technique, Neural Network (NN) is emerging technology that is advancing rapidly and having impact on many scientific and engineering applications. In this paper, NN apply on Asymmetric Cascaded Multilevel Inverter (ACMLI), in order to improve the controller easier to construct, simpler and better performance. To verify these goals, the system simulated based on Matlab Simulink after the NN controller build using m-file program. The simulation results show that the goals can realized.

Neural Network Controller for Power Electronics Circuits

“…The Neural Network seems to have maximum impact on power electronics area that is evident by the publications in the literature [6][7][8][9][10]. NNC is easier to design, simpler, and gives better performance compared to other controllers.…”

Universal Algorithm Control for Asymmetric Cascaded Multilevel Inverter

“…If ACMLI use sine quantization progression [3], each DC voltage can be determined by equation (14). In this equation the voltage of sine wave reference is Vm, the frequency is f, the sequence number of H-Bridge is j and the number of H-Bridge is N).…”

“…The most popular asymmetric CMLI that follow functions are binary (orde-2) and trinary (orde-3) progressions of DC voltages. Others DC progression are equal interval [6] and sine quantization [3]. To implement ACMLI in the various DC voltage progressions and various numbers of H-Bridges, the main problem is control design that consist some control parameters, especially voltage levels, firing angle and switching-state, because nothing researches reported how to determine these parameters.…”

“…Different DC voltage progression also have discussed in [3] and [6]. But in these reference and others not discussed how to determine switching-states for the voltage levels.…”