FPGA-Based Implementation of Finite Set-MPC for a VSI System Using XSG-Based Modeling

Abstract

Finite set-model predictive control (FS-MPC) is used for power converters and drives having unique advantages as compared to the conventional control strategies. However, the computational burden of the FS-MPC is a primary concern for real-time implementation. Field programmable gate array (FPGA) is an alternative and exciting solution for real-time implementation because of the parallel processing capability, as well as, discrete nature of the hardware platform. Nevertheless, FPGA is capable of handling the computational requirements for the FS-MPC implementation, however, the system development involves multiple steps that lead to the time-consuming debugging process. Moreover, specific hardware coding skill makes it more complex corresponding to an increase in system complexity that leads to a tedious task for system development. This paper presents an FPGA-based experimental implementation of FS-MPC using the system modeling approach. Furthermore, a comparative analysis of FS-MPC in stationary αβ and rotating dq frame is considered for simulation as well as experimental result. The FS-MPC for a three-phase voltage source inverter (VSI) system is developed in a realistic digital simulator integrated with MATLAB-Simulink. The simulated controller model is further used for experimental system implementation and validation using Xilinx FPGA: Zedboard Zynq Evaluation and Development Kit. The digital simulator termed as Xilinx system generator (XSG) provided by Xilinx is used for modeling-based FPGA design.

Multivariable Deadbeat Control of Power Electronics Converters with Fast Dynamic Response and Fixed Switching Frequency

“…Hence, more recent solutions involve the MPC problem being reformulated as a multi-parametric algorithm solved offline for all valid states, entailing a lookup table for the optimal solution depending upon the current actual value [3][4][5][6][7]. Due to there being an intrinsic finite set of valid states of power converter that can be applied, an MPC variation, appropriately named Finite Control Set MPC (FCS-MPC), has started to be widely employed [8][9][10]. In this strategy, several system state predictions are made for a finite series of control actions.…”

Model Predictive Base Direct Speed Control of Induction Motor Drive—Continuous and Finite Set Approaches

“…A crucial feature of the MPC is its capability of taking into account the constraints of the control signal and state variables. Still, a main drawback of MPC is its requirement for large computational power [7][8][9][10][11][12][13][14][15][16]. Due to the progress of microprocessor technology it is no longer a critical factor.…”