Search

This article presents a direct model predictive control (MPC) scheme for grid-tied converters (GTCs) with LCL filters operating under nominal and adverse grid conditions. Specifically, the proposed MPC algorithm achieves a high-quality grid current in steady state and fast dynamic responses that characterize direct controllers due to the absence of a dedicated modulator. Thanks to the adopted modeling approach, the control and modulation problems are formulated together as a multiple-input multiple-output (MIMO) problem. In doing so, not only the controller design process is greatly simplified, but also favorable performance in terms of controller bandwidth and robustness is achieved. This is in stark contrast to conventional linear control methods, where the existence of different cascaded and/or parallel control loops oftentimes leads to an adverse interaction with each other. Consequently, as also demonstrated by the presented experimental results, the proposed algorithm achieves superior performance for a wide range of operating conditions, rendering it as a promising control approach for the systems in question.

This article proposes a novel predefined-time sliding mode predictive current control (PDO-SMPCC+HDO) technique to simultaneously enhance disturbance rejection and dynamic response in surface-mounted permanent magnet synchronous motor (SPMSM) drives. Specifically, a composite disturbance predictive model incorporating both slowly varying disturbance and sixth current harmonic disturbance is developed. A predefined-time reaching law (PTRL) and corresponding sliding mode disturbance observer are proposed to effectively estimate the slowly varying disturbance, while the sixth harmonic disturbance is estimated using a frequency-domain harmonic disturbance observer with a specially designed filter. A PTRL-based reference trajectory is defined for the PDO-SMPCC+HDO cost function to adjust the current approach trajectory. Finally, an integrated predictive control scheme is developed by minimizing the cost function. Experimental results on an SPMSM test bench verify the superior disturbance suppression and tracking capabilities of the proposed strategy.

In offshore wind farms connected via diode-rectifier-based high-voltage dc, conventional distributed control strategies have significant coupling among active and reactive power, leading to large oscillations in wind turbine (WT) converter power, voltage, and grid frequency during transients. In this work, we propose a decoupled distributed control strategy based on a novel adaptive virtual impedance (VI) method. In detail, we newly propose a simple estimator to enable each WT controller to locally estimate the global average reactive power, without the need for communication and line impedance knowledge. By comparing the estimated global average value with the actual reactive power, we achieve dynamically adjustable VI, thereby completely decoupling the power control. In addition, a proportional feedforward control is integrated into the estimator, ensuring precise reactive power-sharing among WT converters. We also develop a small-signal model of the proposed method to theoretically confirm the decoupling characteristics, and to facilitate system stability analysis and key control parameters design. Experimental results validate the superior performance of power and frequency regulation during both steady and transient states, in comparison with the existing decoupling control method.

This article proposes a novel solid-state transformer (SST) having a low-frequency medium-voltage ac (LF-MVac) port distinctively, which can be the key equipment for smart distribution networks based on LF-MVac interconnection. The proposed SST has four ports of power-frequency medium-voltage ac (MVac), LF-MVac, low-voltage dc (LVdc), and low-voltage ac (LVac). In addition to the two-level low-voltage dc/ac converter, the proposed SST is mainly composed of an isolated modular multilevel matrix converter (I-M3C), which can achieve single-stage three-port power conversion. First, the topology of the I-M3C is introduced. Then, a simple modulation scheme is provided to achieve single-stage three-port power conversion, and the operating principles of the I-M3C are given in detail. In addition, a control strategy based on dual-dq coordinate system is designed, which can achieve stable operation without the complex multistage coordinated control and voltage-balancing control strategies. Finally, the effectiveness of the proposed control strategy is verified through a 10-kV/2-MW full-power simulation platform, and a 100-V/1-kW scaled-down experimental prototype is built to further demonstrate the correctness of the proposed I-M3C.

Efficiency is a crucial concern for dual active bridge (DAB) converters. Although many studies on novel modulation schemes have attempted to improve the efficiency, achieving the optimal balance between current stress and zero-voltage-switching (ZVS) ability remains challenging. In addition, due to the wide operating range of DABs, small-signal models have to be setup at each equilibrium point to purpose a high performance of liner controllers. Existing works mainly employ the slow-loop to prevent oscillations during transitions, which degrades the dynamic and bandwidth. To address the current state of research, this article proposes a triple-phase-shift modulation combined with model predictive control (MPC) for DABs. Herein, a designed cost function initially calculates shift-angles. Subsequently, a proposed optimization segment for ZVS checks and revises the ZVS ability to select an optimal set of shift angles. The current stress is minimized on the premise that the wide range of ZVS is guaranteed. Meanwhile, the dynamic performance is improved through the nonlinearity of MPC. Finally, a 1.4-kW scaled-down prototype is built, and the experimental comparisons with other schemes verify the effectiveness and superiority of the proposed method.

This article proposes an ultralocal predictive surface-mounted permanent magnet synchronous motor (SPMSM) model-based predefined time sliding mode predictive speed control (UL-SMPC) to achieve exceptional disturbance rejection and tracking performance in SPMSM systems. First, an ultralocal predictive SPMSM model is given, incorporating a time-varying disturbance term and an adaptive control gain. Second, the control gain and disturbance term of the SPMSM model are decoupled and identified, respectively. A control gain optimizer is devised to estimate the control gain, and a predefined time reaching law-based generalized proportional integral observer (PT-GPIO) is developed to estimate the disturbance for each control period. The parameter tuning principles for the control gain optimizer and PT-GPIO are analyzed. Third, a cost index is defined using the predefined time reaching law-based sliding mode surface. Finally, UL-SMPC is synthesized by minimizing the cost index. Experimental results verify the outstanding robustness and tracking performances of the proposed method.

Grid-forming (GFM) converters can support system voltage and frequency, which promotes the integration between distributed generations and power grid. Due to the time delay of digital control, the virtual impedance exhibits opposite damping characteristics on both sides of 1/6 of the sampling frequency (fs/6). The stable operation of GFM converters can be achieved by setting a reasonable damping feedback coefficient in each separate frequency interval. However, the load or line impedance variation may cause the resonant frequency of LC filter to cross the frequency boundary, so GFM converters will not be stable when the resonant frequency is near the frequency boundary. In this article, an improved active damping control with a lead compensator is proposed to achieve positive damping from 0 to fs/4, which eliminates the instability resonant frequency region, and the stability of GFM converters is significantly improved. Then, the procedures of parameter tuning for obtaining the maximum system damping are presented. Furthermore, the discrete-time domain resonant controller is proposed to acquire a high-performance voltage control, which brings a fast transient response without overshoot for output voltage. Finally, experimental results verify the effectiveness of the analysis.

Finite control set model predictive control (FCS-MPC) has gained increasing popularity as an emerging control strategy for electrical drive systems. However, it is still a challenging task to optimize weighting parameters, as multiple objectives are involved in the customized cost function. A cooperative decision-making approach for FCS-MPC is proposed in this article, to solve the optimization problems with manifold control objectives. By splitting the cost function, the optimization problem underlying multiobjective FCS-MPC is separated into a series of decomposed optimization problems. By doing so, the dimension of the decomposed problem is reduced to one. To collect the information for decision-making, an efficient sorting algorithm is applied for each control objective. The theory behind the cooperative decision-making approach is comprehensively analyzed, to validate both the effectiveness and efficiency of the proposed scheme. More specifically, the highlight is the adaptive mechanism on the number of desired candidates, to obtain a decent performance for torque and flux. The candidate that minimizes the switching frequency is selected as the optimal. The proposed scheme is experimentally verified and compared with the existing FCS-MPC without weighting parameters.

Model predictive control (MPC) usually suffers from high computational complexity when it comes to modular multilevel converters (MMCs). Some researchers have attempted to use a modulated approach to reduce the computational burden and improve the control performance. But these methods do not consider the actual physical limitations of the control system, and therefore the control performance degrades at high modulation indices or transients. To solve this problem, a modulated MPC with bound-constrained quadratic programming has been proposed. With this method, the optimal solution of the control problem can be obtained, ensuring a better control performance under high modulation index conditions or in transients. Finally, a comparative experiment with the conventional modulated MPC methods has been carried out. The experimental results validate that the proposed method can achieve superior performance when the MMC operates at high modulation index, transients, and low frequencies.

This article proposes a direct model predictive control (MPC) scheme for asymmetric six-phase permanent magnet synchronous machines (PMSMs), which combines control and modulation in one computation stage. By emulating the switching pattern of space vector modulation (SVM), the MPC problem is formulated as a 4-D current control problem where the switching sequences and instants are computed and directly applied to the inverters. This implicit modulation addresses the issue of a variable switching frequency and spread harmonic spectra of conventional direct MPC methods. Moreover, the effect of the modulation constraints and controller bandwidth on the system performance is investigated as well. To verify the effectiveness of the proposed control strategy, experiments are carried out with an asymmetric six-phase PMSM driven by two three-phase two-level inverters.