Multi-objective fuzzy-decision-making-based FS-MPC with improved performance for grid-connected converters.

In this paper, a multi-objective fuzzy-decision-making-based (MO-FDM) finite-state model predictive control (FS-MPC) method is proposed for improving both steady-state and transient-state operations of the grid-connected converters (GCCs). The main objectives of the proposed method are to achieve the excellent steady-state tracking performance and high dynamics without any weighting factors in the designed controller. Firstly, a repetitive control technique is embedded in the predictive controller, and an integral error term is introduced into the standard cost function used in the GCCs. Secondly, a simple and systematic procedure, which relies on MO-FDM technique, is employed to avoid the selection of weighting factors. As such, this scheme has a good potential to avoid the complicated tuning work while the control performance is not affected. Furthermore, in order to enhance the dynamic response and improve the computational efficiency, a dynamic reference design with a simplified cascade-free FS-MPC strategy is embedded into the predictive controller. Finally, simulation results are presented for demonstrating the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]