Optimized Parameters Initialization of a RMRAC Controller Applied to Grid-Connected Converters

This work aims to present a proposal for optimized initialization of parameters with the aid of meta-heuristics of a Robust Model Reference Adaptive Controller (RMRAC). Since adaptive controllers need their initialization of gains and constants for proper tuning of the controller, and this choice of gains is related to the designer’s experience, the use of optimization algorithms to choose a suitable set of parameters for the controller is viable, because in addition to presenting optimized performance for the application, it becomes independent of the designer’s experience in tuning the parameters. For optimal tuning of the RMRAC, a Genetic Algorithm (GA) is used, and the controller is applied to the current regulation of a singlephase power converter connected to the grid with an LCL filter. Simulation results are presented, which shows the effectiveness of the proposal when compared to a RMRAC initialized empirically by an expert designer.