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.

This paper presents the application of Model Predictive Control (MPC) in high-performance drives. A wide variety of machines have been considered: induction machines, synchronous machines, linear motors, switched reluctance motors, and multiphase machines. The control of these machines has been done by introducing minor and easy-to-understand modifications to the basic predictive control concept, showing the high flexibility and simplicity of the strategy. The second part of the paper is dedicated to the performance comparison of MPC with classical control techniques such as field-oriented control and direct torque control. The comparison considers the dynamic behavior of the drive and steady-state performance metrics such as inverter losses, current distortion in the motor, and acoustic noise. The main conclusion is that MPC is very competitive concerning classic control methods by reducing the inverter losses and the current distortion with comparable acoustic noise.

In this paper, finite-set model-predictive control (FS-MPC) methodologies for a grid-connected three-level neutral-point-clamped converter are investigated. The proposed control strategies produce fixed switching frequency, maintaining all the advantages of predictive control such as fast dynamic response, inclusion of nonlinearities and restrictions, and multivariable control using a single control loop. The first of the proposed FS-MPC strategies is based on a multiobjective cost function, designed to regulate both the inverter currents and the balancing of the dc-link capacitor voltages. The second FS-MPC strategy is derived from the first one, and it is based on a cost function that regulates only the grid current, with the balancing of the capacitor voltages being realized by controlling the duty cycles of the redundant vectors. The proposed control systems are experimentally validated using a 5-kW prototype. The experimental results show a good performance for both strategies, in steady-state and transient response, with a total harmonic distortion lower than 2% for the currents supplied to the grid.

In this work, a model predictive control (MPC) strategy based on optimal switching sequence (OSS) concepts is proposed for a grid-connected three-level neutral-point clamped (3L-NPC) converter. The proposed Cascaded-OSS-MPC (C-OSS-MPC) strategy does not require a weighting factor to balance the dc-link capacitor voltages in the NPC-converter and optimally controls both the grid currents and the capacitor voltages even during disturbances and large step-changes in the references. The resulting MPC strategy allows operating the converter with a predefined harmonic spectrum, relatively low switching frequency and, high and robust dynamic responses in the whole operating range. Moreover, an efficient control algorithm is also addressed to reduce the computational burden typically observed in this kind of MPC strategies. Experimental and simulation results are provided to demonstrate the effectiveness and high-quality performance of the proposed strategy.

The modular multilevel matrix converter is a relatively new power converter topology suitable for high-power alternating current (AC)-to-AC applications. Several publications in the literature have highlighted the converter capabilities, such as full modularity, fault-redundancy, control flexibility and input/output power quality. However, the topology and control of this converter are relatively complex to realise, considering that the converter has a large number of power-cells and floating capacitors. To the best of the authors’ knowledge, there are no review papers where the applications of the modular multilevel matrix converter are discussed. Hence, this paper aims to provide a comprehensive review of the state-of-the-art of the modular multilevel matrix converter, focusing on implementation issues and applications. Guidelines to dimensioning the key components of this converter are described and compared to other modular multilevel topologies, highlighting the versatility and controllability of the converter in high-power applications. Additionally, the most popular applications for the modular multilevel matrix converter, such as wind turbines, grid connection and motor drives, are discussed based on analyses of simulation and experimental results. Finally, future trends and new opportunities for the use of the modular multilevel matrix converter in high-power AC-to-AC applications are identified.

This paper presents two capacitor voltage balancing (CVB) strategies for modular multilevel converter applications. Both balancing schemes are based on model predictive control and are designed to efficiently solve a constrained optimal control problem, where the predicted capacitor voltage errors are included in the cost function with the demanded output voltage of a cluster being forced through an equality constraint. The first method proposed in this work computes specific modulation indexes for each module using the explicit solution of a relaxed version of the original optimization problem. The second approach proposed in this paper reduces the complexity of the original problem by linearising the objective function and using an optimal sorting network based on a greedy algorithm to solve this approximation. Considering the structures of both solution approaches, they are integrated into modulation schemes based on Phase-Shifted and Level-Shifted PWM algorithms, respectively. Experimental results obtained from a nine-cells single-phase MMC prototype demonstrate the good performance achieved with the proposed methodologies, as well as the implementation simplicity offered by the proposed CVB algorithms.