Genetic algorithm optimized fuzzy repetitive controller for low cost UPS inverter application

This paper presents a novel control strategy using a genetic algorithm optimized fuzzy logic controller with repetitive learning action for uninterruptible power supply (UPS) inverter applications. The repetitive learning action can reduce steady-state errors and distortions caused by unknown periodic disturbances. Considering its poor dynamic response with sudden load change, the fuzzy logic controller (FLC) is introduced. The parameters for the FLC are optimized by genetic algorithm (GA) in the proposed scheme. The presented digital control scheme measure only the output voltage, decreasing the amount of sensors and the overall system cost. The control laws and design procedure of the control scheme are discussed. Simulation and experimental results for a single-phase UPS inverter controlled by a TMS320F240 DSP are presented to verify the performance of the proposed control approach under different load conditions. It proves to be a cost-effective solution for common UPS products