Conventional Model Predictive Control (MPC) for Active Neutral Point Clamped (ANPC) converters requires a complex tuning of weighting factors in its multi-objective cost function. This paper proposes a Sequential Predictive Current Control (SPCC) strategy that eliminates the need for such weighting factors, simplifying controller design for reactive power compensation applications. The proposed method employs a two-stage sequential optimization: first, it identifies a candidate subset of switching states that minimizes current tracking error, and second, it selects the optimal state from this subset to ensure DC-link capacitor voltage balancing. The resulting optimal voltage reference is synthesized by a standard Pulse Width Modulation (PWM) stage, which ensures a fixed switching frequency and improves the harmonic spectrum compared to direct MPC methods. This sequential approach decouples the control objectives, offering a simpler and more robust tuning process. Simulation studies validate the strategy, demonstrating excellent reference current tracking and robust voltage balancing while maintaining low harmonic distortion in the source current.

This paper proposes a Sequential Model-Based Predictive Current Control (SMBPC) integrated with Space Vector Modulation (SVM) for reactive power compensation in three-level Neutral Point Clamped (NPC) inverters. The sequential approach optimizes reference current selection and capacitor voltage balance, employing a two-stage cost function to minimize voltage imbalance. Additionally, this work approach obviates the need for weighting factors, as the cost function is not multi-objective, streamlining the optimization process and reducing computational complexity. Simulation studies are provided to show the effectiveness of this proposal demonstrating accurate current reference tracking.

This paper presents a delay-compensated modulated model predictive direct power control (DC-M2PDPC) strategy for grid-connected three-level neutral-point-clamped (3L-NPC) converters. The proposed method integrates power-oriented control, fixed-frequency modulation, and control delay compensation within a predictive control scheme. The DC-M2PDPC strategy achieves fast dynamic response and demonstrates superior steady-state performance in power tracking and DC-link voltage balancing. It also ensures lower harmonic content than conventional methods, even under dynamically varying power conditions, in accordance with the IEEE 519-2022 Standard for Harmonic Control in Electrical Power Systems. These features make it well-suited for grid-tied applications such as wind energy conversion systems (WECS) and photovoltaic (PV) systems.

Multiphase electric drive systems, which consist of power electronic converters and multiphase machines (with n greater than 3), have become a reliable solution for various high-power industrial needs, including propulsion systems for electric ships, vehicles and renewable energy applications, due to their phase redundancy. However, fully exploiting their inherent benefits requires more sophisticated control techniques. The finite control set model predictive control has emerged as a suitable strategy due to its ease of implementation and applicability across different systems. Nevertheless, tuning the weighting factor in the cost function significantly impacts control outcomes, making it an important aspect to consider. In this context, novel control techniques named Sequential Model Predictive Control (SMPTC) and Sequential Model Predictive Control based on Virtual Vectors (SMPTC-VV) have emerged as viable alternatives. Both methods eliminate weighting factors by using simple cost functions applied sequentially. SMPTC-VV integrates virtual vectors to reduce the secondary-plane currents, decreasing vibrations in induction machines. Despite the recent introduction of SMPTC and SMPTC-VV strategies, studies comparing the performance of these controllers have not yet been conducted. Therefore, this article presents a comparative study of these control techniques.