Implementation Strategy for Resource Optimization of FPGA-Based Adaptive Finite Control Set-MPC Using XSG for a VSI System

Abstract

Finite control set-model predictive control (FCS-MPC) for the power electronic systems has been implemented using the field-programmable gate array (FPGA), considering an alternative solution to handle the computational burden of the control algorithm. However, FPGA resource utilization is a concern for optimum design and development of the FCS-MPC. This article presents analytical approach-based implementation strategies using the Xilinx system generator (XSG), considering the real-time operation of the FCS-MPC for a three-phase voltage source inverter (VSI). Moreover, an adaptive prediction model is proposed to adapt to the change in the load current. The percentage total harmonic distortion (THD), dynamic response, and steady-state error are evaluated for system-performance analysis. The implementation strategies are compared based on FPGA resource utilization for the FCS-MPC in the stationary αβ- and rotating dq-frames considering the fixed, approximated, and adaptive values of a coefficient used for current prediction. The lookup tables (LUTs), flip-flops, and digital signal processor (DSP) slices have been opted as the utilization indices of the FPGA resources for comparative analysis. The optimum design-based controller model is used for FPGA-based experimental system implementation. The simulation and experimental results are used for the performance evaluation of the FCS-MPC in both αβ- and dq -frames. Moreover, change in the switching-state constraint is included in the cost function and controller performance is evaluated corresponding to the weighting factor for the approximated and adaptive coefficient values.