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In this article, an efficient model predictive control (MPC) using virtual voltage vectors for three-phase three-level converters is proposed. The proposed MPC achieves constant switching frequency by applying four voltage vectors, including one virtual voltage vectors and three other voltage vectors, in each control cycle. In addition, to reduce the computational burden, two-stage MPC approach is adopted. The first stage chooses one of six medium voltage vectors that minimizes the cost function. Then, in the second stage, these voltage vectors including virtual voltage vectors, which locate the same sector with the optimal medium voltage vector, are involved in the MPC optimization. The advantages of the proposed MPC over the classical MPC have been validated through experimental results. [ABSTRACT FROM AUTHOR]

An improved two-stage model predictive current control (MPCC) for three-phase three-level converters in the paper, which can simultaneously achieve common-mode voltage (CMV) reduction, effective dc-link capacitor voltage control, and decreased computational burden, is proposed. Compared to the other current control strategies, it has the capability of handling multiple control objectives and possesses a simple structure. Furthermore, it greatly reduces the CMV since the peak CMVs of all the candidate voltage vectors are constrained to be less than one sixth of the dc-link voltage. In addition, an optimal two-stage voltage vector selection mechanism is employed in the proposed method. It helps to significantly reduce the computational complexity. Simulation and experimental results are provided to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents a novel model predictive control (MPC) for the T-type single-phase three-level inverters. The cumbersome procedure in tuning of weighting factors is eliminated so that the implementation of the proposed MPC becomes easy. The constant switching frequency is achieved during the control implementation in order to facilitate the filter design. In order to optimize the distribution of the output current harmonics, multiple voltage vectors are employed in each control cycle with their application times setting inversely proportion to the respective cost function. The redundant small voltage vectors are utilized to balance the neutral point voltage of the inverter by directly regulating the upper and lower dc-link capacitors voltages. Finally, the proposed MPC algorithm is experimentally evaluated and compared with other two unfixed switching frequency MPC algorithms in terms of the steady state, transient performance, and parameter sensitivity. [ABSTRACT FROM AUTHOR]

Model predictive control (MPC) suffers from high computational burden and cumbersome tuning of weighting factors especially for three-level three-phase inverters. Here, a fast finite-switching-state MPC (FSS-MPC) algorithm without weighting factors is proposed. First, the deadbeat control is used to construct the voltage vector reference. Then, the T-type three-level three-phase inverter topology is selected and voltage vectors are carefully tuned in order to minimize the neutral-point (NP) voltage fluctuation. The voltage vectors that are far from the desired voltage vector reference and go against balancing the NP voltage will not participate in the cost function optimization. Thus, only 3 effective voltage vectors instead of totally 27 vectors are required in the implementation of the proposed FSS-MPC algorithm, which saves computation time up to 53.3%. Furthermore, the proposed algorithm makes the tuning of the weighting factor unnecessary, which simplifies the practical implementation and improves the portability of the algorithm. Finally, an experimental prototype was established and main results including the steady-state and dynamic performance were presented to validate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]