Suboptimal multirate MPC for five-level inverters

TL;DR

This paper proposes a multirate model predictive control algorithm for five-level inverters that reduces harmonic distortion by allowing multiple control updates within a sampling period, balancing performance and computational complexity.

Contribution

It introduces a suboptimal multirate MPC method for multilevel inverters, enabling multiple control updates per sampling period to improve harmonic performance.

Findings

Significant reduction in harmonic distortion achieved.

Increased number of commutations compared to standard MPC.

Validated through simulation on a five-level diode-clamped inverter.

Abstract

The application of multilevel converters to renewable energy systems is a growing topic due to their advantages in energy efficiency. Regarding its control, model predictive control (MPC) has become very appealing due to its natural consideration of discrete inputs, its optimization capability, and the present-day availability of powerful processing hardware. The main drawback of MPC compared to other control techniques in this field is that the control input is held constant during the sampling period, and it is usually difficult or even impossible to reduce this sampling period because of hardware limitations. For this reason, a multirate MPC algorithm is proposed, which allows to change the control input several times within the sampling period. The optimization problem is simplified and made suboptimal to substantially decrease computational burden. This approach is tested in simulation on a three-phase, five-level diode-clamped converter (DCC) operating in inverted mode with a three-phase resistive load. Results show significant reduction in harmonic distortion at the cost of an increase in the number of commutations with respect to a standard MPC operating at the same sampling period.