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Robust model predictive control for three-level voltage source inverters

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Abstract

To solve the problem of parameter mismatch in model predictive control (MPC), this paper presents a robust model predictive control method based on a fixed window optimization (FWO) algorithm for a three-level voltage source inverter that only needs to sample the current value. When compared with the traditional observer-based model predictive control (such as the Luenberger observer, sliding mode observer (SMO) and Kalman filter (KMF)), the proposed method does not require an observer with a complicated design, and its algorithm is simple and easy to understand. Meanwhile, high current sampling accuracy is not needed in the proposed method. However, it is necessary in some types of model-free predictive control. In addition, low switching frequency operation and delay compensation are also considered in this paper. In general, the proposed method is simple to implement and does not have high requirements in terms of the accuracy of its current sensor. Experimental results show that the proposed method can accurately estimate parameter values and improve the parameter robustness of MPC.

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Acknowledgements

This research is supported by the National Natural Science Foundation of China (51677049).

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Authors and Affiliations

  1. School of Electric Engineering and Automation, Hefei University of Technology, Hefei, China

    Jianfeng Hong, Xing Zhang & Renxian Cao

  2. National and Local Joint Engineering Laboratory for Renewable Energy Access to Grid Technology, Hefei University of Technology, Hefei, China

    Jianfeng Hong, Xing Zhang & Renxian Cao

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  1. Jianfeng Hong
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  2. Xing Zhang
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  3. Renxian Cao
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Correspondence to Jianfeng Hong.

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Hong, J., Zhang, X. & Cao, R. Robust model predictive control for three-level voltage source inverters. J. Power Electron. 21, 747–756 (2021). https://doi.org/10.1007/s43236-021-00230-y

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  • DOI: https://doi.org/10.1007/s43236-021-00230-y

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