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.

Highlights

  • Model predictive control (MPC) possess appealing characteristics such as flexibility of simultaneous handling of multiple constraints and easy inclusion of nonlinearities [1,2,3,4]

  • The digital simulator termed as Xilinx system generator (XSG) provided by Xilinx is used for modeling-based Field programmable gate array (FPGA) design

  • MPC has been applied for two-level voltage source inverter (VSI) [5,6], three-level neutral-point clamped converter (NPC) [2,7], active front end rectifier [8,9], cascaded H-Bridge inverter [10,11,12], asymmetric flying capacitor converter [13], three-phase direct Matrix converters [14,15], predictive control for UPS

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Summary

Introduction

Model predictive control (MPC) possess appealing characteristics such as flexibility of simultaneous handling of multiple constraints and easy inclusion of nonlinearities [1,2,3,4]. The controller development approach is crucial considering the FPGA-based real-time system implementation with an aspect of the straightforward utilization of the product in industrial applications. Xilinx system generator (XSG) as a digital simulator adopting MBD platform was used for the step-by-step design and modeling of the FS-MPC algorithm in αβ-frame in [31] for the load current control of three-phase VSI system. This paper presents the FPGA-based real-time implementation of FS-MPC for experimental validation of controller modeled in the digital simulator (XSG). The FS-MPC is developed for a phase VSI system with RL load using an optimization function consisting of current control objectives three-phase VSI system with RL load using an optimization function consisting of current control considering both stationary αβ and rotating dq reference frames for comparative analysis.

Finite
Discrete-Time Predictive Model
Selection Criteria
Computation of Cost Functions
Selection of Optimum Switching State
Generation
Results
System Performance
Simulation
Intermediate
Experimental
Design
System
Considering
Intermediate Response
15. Experimental
Conclusions
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