Improved Model-Free Predictive Current Control With Forgetting Factor

An improved model-free predictive current control with forgetting factor (IMFPCCFF) is presented in this article. The main advantages of previous model-free predictive current control (MFPCC) are that it is only based on detecting the load currents and the current differences. It does not require any parameter of the system. However, this approach has noticeable disadvantages: high requirements on sampling accuracy increase system cost and reduce system reliability, and the reduction of sampling interval in high-frequency converters amplifies sampling noise in adjacent current increment calculations. This article utilizes more historical data to suppress the impact of sampling noise on system performance while introducing a forgetting factor to cope with changes in operating conditions. The feasibility and superiority of the proposedmethod are verified by experiments.

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Publication Details

Journal
IEEE Transactions on Industrial Electronics
Published
2025-06-02
DOI
https://doi.org/10.1109/tie.2025.3569963
Citations
1
Primary Topic
Multilevel Inverters and Converters
Type
article
Field-Weighted Citation Impact
0.73
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article

Improved Model-Free Predictive Current Control With Forgetting Factor

Xiang Wu, Xinbo Cai, Yaofei Han, Zhixun Ma et al.
1 citations
IEEE Transactions on Industrial Electronics
Multilevel Inverters and Converters
0.73
article

Improved Model-Free Predictive Current Control With Forgetting Factor

Xiang Wu, Xinbo Cai, Yaofei Han, Zhixun Ma, Guobin Lin, Xu Zhang
article en
1 citations

Abstract

An improved model-free predictive current control with forgetting factor (IMFPCCFF) is presented in this article. The main advantages of previous model-free predictive current control (MFPCC) are that it is only based on detecting the load currents and the current differences. It does not require any parameter of the system. However, this approach has noticeable disadvantages: high requirements on sampling accuracy increase system cost and reduce system reliability, and the reduction of sampling interval in high-frequency converters amplifies sampling noise in adjacent current increment calculations. This article utilizes more historical data to suppress the impact of sampling noise on system performance while introducing a forgetting factor to cope with changes in operating conditions. The feasibility and superiority of the proposedmethod are verified by experiments.

IEEE Transactions on Industrial ElectronicsVol. 72(12)
Tongji University (CN), China University of Mining and Technology (CN)
Openalex Percentile: Top 28%
Multilevel Inverters and Converters
0.73
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Improved Model-Free Predictive Current Control With Forgetting Factor — Xiang Wu, Xinbo Cai, et al. · IEEE Transactions on Industrial Electronics (2025) | TGRS Research Map | TGRS