RBF Neural Network-Based Sliding Mode Control for Modular Multilevel Converter with Uncertainty Mathematical Model
For medium and high-powered applications, modular multilevel converters have become the most promising converter application. In this paper, a sliding mode controller based on an RBF neural network is proposed for a modular multilevel converter. The RBF neural network is designed to approximate the...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-02-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/15/5/1634 |
| _version_ | 1797475275021221888 |
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| author | Xuhong Yang Haoxu Fang |
| author_facet | Xuhong Yang Haoxu Fang |
| author_sort | Xuhong Yang |
| collection | DOAJ |
| description | For medium and high-powered applications, modular multilevel converters have become the most promising converter application. In this paper, a sliding mode controller based on an RBF neural network is proposed for a modular multilevel converter. The RBF neural network is designed to approximate the uncertainty mathematical model of a modular multilevel converter. The main innovation of the proposed method is that it does not require any model parameters and control parameters during the whole control process. This means that parameter changes caused by the external environment will not influence the controller performances. Finally, by comparing with a conventional PI controller, the simulation proves the feasibility and effectiveness of the proposed control method. In addition, the experimental results show that the grid-side current can become stable immediately while the active power is stabilized after 20 ms when the set value is changed. |
| first_indexed | 2024-03-09T20:41:49Z |
| format | Article |
| id | doaj.art-5f007b615701415c86f3c06eba1e81bd |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T20:41:49Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-5f007b615701415c86f3c06eba1e81bd2023-11-23T22:55:12ZengMDPI AGEnergies1996-10732022-02-01155163410.3390/en15051634RBF Neural Network-Based Sliding Mode Control for Modular Multilevel Converter with Uncertainty Mathematical ModelXuhong Yang0Haoxu Fang1College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, ChinaCollege of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, ChinaFor medium and high-powered applications, modular multilevel converters have become the most promising converter application. In this paper, a sliding mode controller based on an RBF neural network is proposed for a modular multilevel converter. The RBF neural network is designed to approximate the uncertainty mathematical model of a modular multilevel converter. The main innovation of the proposed method is that it does not require any model parameters and control parameters during the whole control process. This means that parameter changes caused by the external environment will not influence the controller performances. Finally, by comparing with a conventional PI controller, the simulation proves the feasibility and effectiveness of the proposed control method. In addition, the experimental results show that the grid-side current can become stable immediately while the active power is stabilized after 20 ms when the set value is changed.https://www.mdpi.com/1996-1073/15/5/1634modular multilevel convertersliding mode controlRBF neural networkuncertainty mathematical model |
| spellingShingle | Xuhong Yang Haoxu Fang RBF Neural Network-Based Sliding Mode Control for Modular Multilevel Converter with Uncertainty Mathematical Model Energies modular multilevel converter sliding mode control RBF neural network uncertainty mathematical model |
| title | RBF Neural Network-Based Sliding Mode Control for Modular Multilevel Converter with Uncertainty Mathematical Model |
| title_full | RBF Neural Network-Based Sliding Mode Control for Modular Multilevel Converter with Uncertainty Mathematical Model |
| title_fullStr | RBF Neural Network-Based Sliding Mode Control for Modular Multilevel Converter with Uncertainty Mathematical Model |
| title_full_unstemmed | RBF Neural Network-Based Sliding Mode Control for Modular Multilevel Converter with Uncertainty Mathematical Model |
| title_short | RBF Neural Network-Based Sliding Mode Control for Modular Multilevel Converter with Uncertainty Mathematical Model |
| title_sort | rbf neural network based sliding mode control for modular multilevel converter with uncertainty mathematical model |
| topic | modular multilevel converter sliding mode control RBF neural network uncertainty mathematical model |
| url | https://www.mdpi.com/1996-1073/15/5/1634 |
| work_keys_str_mv | AT xuhongyang rbfneuralnetworkbasedslidingmodecontrolformodularmultilevelconverterwithuncertaintymathematicalmodel AT haoxufang rbfneuralnetworkbasedslidingmodecontrolformodularmultilevelconverterwithuncertaintymathematicalmodel |