Multi-Step Predictive Current Control for NPC Grid-Connected Inverter

Yu, Yunjun; Wang, Xianzheng

doi:10.1109/access.2019.2950107

Cited by 13 publications

(9 citation statements)

References 32 publications

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“…Therefore, it is necessary to expand the prediction time domain. In [38,39], the multi-step prediction methods are proposed which aims to obtain the optimal variables in multiple sampling instants. It should be a meaningful work to apply the multi-step predictive control to the TSMC in future.…”

Section: Discussionmentioning

confidence: 99%

Vector Modulation-Based Model Predictive Current Control with Filter Resonance Suppression and Zero-Current Switching Sequence for Two-Stage Matrix Converter

Zhang

2021

Energies

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This paper proposes a novel model predictive current control scheme for two-stage matrix converter. The switching frequency is kept constant by fixing the switching instant. The control strategy achieves to control source reactive power in the input side and output currents in the output side. In addition, the advantage of the proposed strategy compared with conventional model predictive control is firstly proved using the principle of vector synthesis and the law of sines in the vector distribution area. Moreover, a zero-current switching sequence is proposed and implemented to insure zero-current switching operations and reduce the switching losses. Furthermore, in order to suppress the input filter resonance, which is easier to be inspired by the model predictive control, compared with traditional control strategies, an innovative active damping technique is proposed and implemented. Finally, both simulation and experiment are implemented to verify the performance of the proposed strategy. The results demonstrate that the control system features both good steady and transient performance.

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Section: Discussionmentioning

confidence: 99%

Vector Modulation-Based Model Predictive Current Control with Filter Resonance Suppression and Zero-Current Switching Sequence for Two-Stage Matrix Converter

Zhang

2021

Energies

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“…The problems that are encountered by the two strategies are that the switching of frequency fails to maintain stability, and the total harmonic distortion is high. As the performance of digital processors improves, model predictive control (MPC) has been introduced to the control technology for grid-connected inverters [8][9][10][11]. MPC can omit the current inner loop control and pulse width modulation, yielding effortless application and strong adaptability.…”

Section: Introductionmentioning

confidence: 99%

Low Current Ripple Parameter-Free MPCC of Grid-Connected Inverters for PV Systems

Yin¹,

et al. 2023

Applied Sciences

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With an emphasis placed on a low-carbon economy, photovoltaic grid-connected inverters are moving toward the center of the stage. In order to address the problems related to the strong parameter dependence of the conventional model’s predictive control in grid-connected inverters, an improved parameter-free predictive current control is proposed. Relying on an extended state observer, an ultralocal model is employed to predict future currents without any parameters. The system can achieve a satisfactory performance in terms of dynamic response and robustness. Additionally, 30 virtual voltage vectors are extended for lower current ripples, which is followed by the use of a triangle candidate strategy to significantly ease the computing burden. In general, the proposed strategy omits parameter dependence, complex tuning work, and large tracking errors. The effectiveness of the proposed model is verified through the experimental results.

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“…Refs. [20,21] can also achieve a better output performance by adopting multi-step prediction. Here, the multi-step prediction is equivalent to expanding the vector set.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical search approach based online model predictive control of three‐level converter fed PMSM driving systems

Guan

Zhen

Yan

et al. 2022

IET Power Electronics

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The finite‐control‐set model predictive control (FCS‐MPC) can achieve a high output and fast control response. However, the size of the candidate vector set of FCS‐MPC must be very huge to achieve a satisfactory steady‐state control performance. Although some studies suggest that the candidate vector set can be expanded by increasing the number of vectors in one period or directly defining new virtual vectors, there is a tricky contradiction between improving the steady‐state control performance and reducing the computational burden. It makes the online realization difficult. This study presents a hierarchical search approach based FCS‐MPC of three‐level converter fed permanent magnet synchronous motor (PMSM) driving systems. The optimal vector is obtained by continuously shrinking the vector space, so that only 30 prediction calculations are needed to evaluate more than 20,000 candidate vectors. Consequently, the proposed method can achieve the excellent steady‐and transient‐state control performance online. Moreover, since the optimal vector is chosen directly from the vector set, the linear‐and over‐modulation are unified. No special treatment is necessary for over‐modulation driving systems, because the reference voltage is decided naturally by the cost function of FCS‐MPC. Some experimental results are shown finally to prove the correctness and feasibility of the proposed method.

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Multi-Step Predictive Current Control for NPC Grid-Connected Inverter

Cited by 13 publications

References 32 publications

Vector Modulation-Based Model Predictive Current Control with Filter Resonance Suppression and Zero-Current Switching Sequence for Two-Stage Matrix Converter

Vector Modulation-Based Model Predictive Current Control with Filter Resonance Suppression and Zero-Current Switching Sequence for Two-Stage Matrix Converter

Low Current Ripple Parameter-Free MPCC of Grid-Connected Inverters for PV Systems

Hierarchical search approach based online model predictive control of three‐level converter fed PMSM driving systems

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