An Evolutionary-based Parametrization of Robust Adaptive Second-Order Sliding Mode Controller Applied on Grid-injection Control of Grid-tied Converters with LCL Filter

Abstract

This work presents an evolutionary-based parametrization for a new discrete-time robust adaptive second-order sliding mode controller. The automatic design procedure is performed using a genetic algorithm. The novel controller is based on robust model reference adaptive control theory and a super-twisting algorithm. The resulting controller is applied to a grid-tied converter with an LCL filter. The proposed design approach, a meta-heuristic algorithm inspired by natural processes, aims to enhance the initial controller’s performance by automating the selection of the controller parameters. Simulation results using PSIM, including converter switching and converter synchronization, are presented to validate the effectiveness of the control strategy, showcasing improved performance in reducing initial transients and enhancing steady-state operation compared to the controller based on designer experience.