The application of model predictive control in electrical drives has been studied extensively in the past decade. This article presents what the authors consider the most relevant contributions published in the last years, mainly focusing on three relevant issues: weighting factor calculation when multiple objectives are utilized in the cost function, current/torque harmonic distortion optimization when the power converter switching frequency is reduced, and robustness improvement under parameters uncertainties. Therefore, this article aims to enable readers to have a more precise overview while facilitating their future research work in this exciting area.

An active power filter implemented with a four-leg voltage-source inverter using a predictive control scheme is presented. The use of a four-leg voltage-source inverter allows the compensation of current harmonic components, as well as unbalanced current generated by single-phase nonlinear loads. A detailed yet simple mathematical model of the active power filter, including the effect of the equivalent power system impedance, is derived and used to design the predictive control algorithm. The compensation performance of the proposed active power filter and the associated control scheme under steady state and transient operating conditions is demonstrated through simulations and experimental results.

The implementation of multistep direct model predictive control (MPC) for dc-dc boost converters overcomes the well-known issue of nonminimum phase behavior. However, it can lead to a high computational burden depending on the prediction horizon length. In this paper, a simple and computationally efficient MPC method for dc-dc boost converters is proposed. The key novelty of the presented control strategy lies in the way dynamic references are handled. The control strategy is capable of providing suitable references for the inductor current and the output voltage, without requiring additional control loops. Moreover, this reference design allows the predictive controller to be implemented with a single-step prediction horizon. Thus, a significant reduction in the required real-time calculations executed in the control hardware is achieved. To obtain constant switching frequency, the power switch commutation instants within a sampling period are considered as control inputs. Therefore, the predictive controller is formulated as a continuous control set MPC. Additionally, the proposed formulation is able to deal with different operation modes of the converter without changing the controller structure. Finally, an observer is used to dynamically modify the reference to provide robustness to system parameter uncertainties. Simulation and experimental results show an accurate tracking of dynamic inductor current and output voltage references, while respecting the restrictions on maximum inductor current levels of the converter.

In this paper, a model predictive control (MPC) based on optimal switching sequences (OSSs) for a single-phase grid-connected full-bridge neutral-point-clampled (NPC) power converter is presented. The predictive control algorithm is formulated in terms of OSSs, which was originally proposed to govern three-phase power converters. In this paper, the OSS concept is extended to control single-phase power converters. The proposed MPC algorithm belongs to the continuous control set MPC and is able to provide fixed switching frequency while handling system constraints. The proposed algorithm has been experimentally tested in an NPC power converter prototype. Experimental results show the desired fixed switching behavior in the steady-state condition and the intrinsic fast dynamic provided by MPC during transients. Furthermore, the test outcomes demonstrate the robustness of the proposed controller under large system parameter deviations.

In this study, a model predictive control (MPC) strategy that combines finite-control-set MPC with selective harmonic elimination (SHE) modulation pattern in its formulation is proposed to govern multilevel power converters. Based on a desired operating point for the system state (converter current reference), an associated predefined SHE voltage pattern is obtained as a required steady-state control input reference. Then, the cost function is formulated with the inclusion of both system state and control input references. According with the proposed reference and cost function formulation, the predictive controller prefers to track the converter output current reference in transients, while preserving the SHE voltage pattern in steady state. Hence, as evidenced by experimental results, a fast dynamic response is obtained throughout transients while a predefined voltage and current spectrum with low switching frequency is achieved in steady state.

A single-objective predictive control method that deals with four main control objectives applied to a multivariable single-phase three-level neutral-point-clamped converter operating as an active power filter is proposed in this paper. The four control objectives are to self-support the dc-bus voltage under load variations, to compensate the reactive power and the current harmonics, and to balance the dc capacitor voltages by using a predefined combination of the redundant switching states of the converter. The main contribution of the proposed method is that these objectives are accomplished without using weighting factors in the cost function, which eliminates problems such as multiobjective optimization or additional empirical procedures for determination of these factors. As a result, the method is easy to implement and rapidly selects the optimal voltage to improve the dynamic-state performance. Experimental results from a 2-kVA prototype are presented to prove that the method is valid for single-phase compensation. The well-known effect of model parameter errors' issue, which is inherent in predictive control methods, is also tested to confirm that the harmonic distortion in the grid current is below 5% even when the predictive model has a 25% error between actual and theoretically estimated grid impedance values.