High performance operation for a four-leg NPC inverter with two-sample-ahead predictive control strategy

• We propose a finite control-set model predictive control strategy with two-sample-ahead.
• We propose a novel discrete-time model that considers the LC filter and the neutral inductor.
• We propose a strategy to reduce the number of calculations, switching frequency, and computational burden.

In this paper is proposed a finite control-set model predictive control (FCS-MPC) strategy which uses a two-sample-ahead prediction horizon to achieve high-performance operation for a three-phase four-leg neutral-point-clamped (NPC) inverter with an output LC filter. The control strategy is proposed in order to minimize the error between the output voltages and their references, maintain equal voltage among the dc-link capacitors, and reduce the overall switching frequency of the inverter. One-sample-ahead and two-sample-ahead prediction horizon are evaluated and compared in terms of reference tracking error and THD, under steady-state and transient operating conditions with linear and non-linear loads. The experimental results demonstrate that the proposed two-sample-ahead prediction horizon is more suitable for high power applications where lower switching frequency operation is mandatory.