Optimization of Scaling Factors of Fuzzy-Logic Controller for CVCF Inverter by Genetic Algorithm

A novel fuzzy logic controller with repetitive learning action for CVCF inverters is presented in this paper The repetitive learning action can reduce steady-state errors and distortions caused by unknown periodic disturbances, and the fuzzy logic controller (FLC) is used to improve its poor dynamic response with sudden load change. The scaling factors for the FLC are optimized by genetic algorithm (GA) in the proposed scheme. The control laws and design procedure of the control scheme are discussed. Simulation and experimental results for a single-phase CVCF inverter controlled by a TMS320F240 DSP are presented to verify the performance of the proposed control approach under different load conditions.