Abstract
This work presents hysteresis control applied to UXE-type inverter topology with a PI (Proportional Integral) controller, where the gains are derived by Particle Swarm Optimization (PSO). The investigated UXE inverter can generate a thirteen-level output voltage waveform, which results in lower switching losses. It can boost the output voltage to 1.5 times the applied input DC source voltage. Satisfactory inverter operation is ensured by employing twelve-band hysteresis current control. The tuning of the PI controller required for the closed-loop hysteresis current control is achieved by nature-inspired PSO algorithm. A comparative analysis is also performed after obtaining the results applying nature-inspired PSO and conventional Ziegler Nichols (ZN) methods. The effectiveness of the control strategy is verified in the MATLAB Simulink and further validated in experiment using TMS320F28379D and also with Typhoon Hardware in Loop Technology.
Highlights
Medium voltage multilevel inverters (MLI) have gained popularity in recent years
This paper presents hysteresis control of a thirteen-level switched capacitor inverter where the PI controller parameter tuning is performed using metaheuristic particle swarm optimization (PSO)
This paper finds the gain constants' values by using the nature-inspired particle swarm optimization (PSO) technique
Summary
Medium voltage multilevel inverters (MLI) have gained popularity in recent years. These are widely used for renewable energy integration because of theirbetter performance. Their applications has included electric vehicles and power conditioning units [1]-[2].In the MLIs, the switches voltage stressreduces to a considerable level, and the output voltage waveform with reduced THD is achieved [3]. In CHB-MLI, as the number of voltage levels increase, the number of isolated. This paper finds the gain constants' values by using the nature-inspired particle swarm optimization (PSO) technique. The metaheuristic-based nature-inspired optimization techniques can fine-tune the gains of the PI controllers by obtaining optimum solutions
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