Improved Model-Free Predictive Control of a Three-Phase Inverter

Abstract

Model predictive control (MPC) performance depends on the accuracy of the system model. Moreover, the optimization algorithm of MPC requires numerous online computations. These inherent limitations of MPC hinder its application in power electronics systems. This paper proposes a two-part solution for these challenges for a three-phase inverter with an output LC filter. The first part of the control scheme is a linear and modified model-free approach based on the auto-regressive structure (ARX) with exogenous input. The second part is the computationally efficient optimization algorithm based on the active set method to solve the optimization problem of the MFPC. The objective of the control scheme is to regulate the output voltages of the inverter in the presence of constraints. The constraints are the maximum admissible filter current and optimal duty cycle to avoid any damage to the system. To validate the performance of the proposed control scheme, simulations and hardware-in-loop (HIL) real-time investigations have been performed, comparing the results of the proposed approach with the model-based predictive control. The results showcase the computational efficiency and effectiveness of the MFPC approach, demonstrating its potential for overcoming the limitations of traditional MPC in power electronics systems.