Optimizing LQG Controller for a Single-Phase Power Inverter in an AC Microgrid System

This article presents an optimization-based Linear Quadratic Gaussian (LQG) control application for controlling a single-phase power inverter in an ac micro-grid system. Several optimization techniques (e.g., genetic algorithm, particle swarm optimization, grey wolf optimization, pattern search optimization, and whale optimization) have been applied with two different objective functions (i.e., ITAE and RMSE) to prove the effectiveness of different optimizers for enhancing control performance. A comparative analysis between the different optimizers has been presented based on their optimization performance and controller performances. From the comparison presented grey wolf optimization outperforms the other studied optimizers with only 2.89% & 2.04% overshoots and 0.07 & 0.30% steady-state error with ITAE and RMSE objective functions respectively. The simulations and optimizations are conducted in MATLAB/ Simulink environment.