Model Predictive Control Based Type-3 Fuzzy Estimator for Voltage Stabilization of DC Power Converters
The stability of power electronic devices is prone to instability when supplying constant power loads (CPL) due to their negative impedance specifications. This necessitates an efficient control methodology to overcome the destabilization issue and regulate the response of the output voltage. In par...
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| Veröffentlicht in: | IEEE transactions on industrial electronics (1982) 2022-12, Vol.69 (12), p.13849-13858 |
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| container_title | IEEE transactions on industrial electronics (1982) |
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| creator | Gheisarnejad, Meysam Mohammadzadeh, Ardashir Khooban, Mohammad-Hassan |
| description | The stability of power electronic devices is prone to instability when supplying constant power loads (CPL) due to their negative impedance specifications. This necessitates an efficient control methodology to overcome the destabilization issue and regulate the response of the output voltage. In particular, this article proposes a novel interval type-III fuzzy neural network-based model predictive control (IT3FNNMPC) to mitigate the destructive effects of CPL in dc/dc boost converters implemented in the microgrid (MG) and power system distribution. In a typical MGs configuration, the IT3FNNMPC controller is formulated and designed in a constraint control problem to achieve a fast-transient response of system voltage. The feasibility and applicability of the designed IT3FNNMPC controller have been validated by hardware-in-the-loop real-time simulations. |
| doi_str_mv | 10.1109/TIE.2021.3134052 |
| format | Article |
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This necessitates an efficient control methodology to overcome the destabilization issue and regulate the response of the output voltage. In particular, this article proposes a novel interval type-III fuzzy neural network-based model predictive control (IT3FNNMPC) to mitigate the destructive effects of CPL in dc/dc boost converters implemented in the microgrid (MG) and power system distribution. In a typical MGs configuration, the IT3FNNMPC controller is formulated and designed in a constraint control problem to achieve a fast-transient response of system voltage. The feasibility and applicability of the designed IT3FNNMPC controller have been validated by hardware-in-the-loop real-time simulations.</description><identifier>ISSN: 0278-0046</identifier><identifier>EISSN: 1557-9948</identifier><identifier>DOI: 10.1109/TIE.2021.3134052</identifier><identifier>CODEN: ITIED6</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Control methods ; Control systems ; Control systems design ; Controllers ; DC power converters ; Destabilization ; Distributed generation ; Electric potential ; Electric power distribution ; Electric power systems ; Electronic devices ; Fuzzy control ; Fuzzy logic ; Hardware-in-the-loop simulation ; interval fuzzy type-III ; model predictive control (MPC) ; nonideal constant power loads (CPL) ; Power converters ; Power electronics ; Power system stability ; Predictive control ; Pulse width modulation ; Stability analysis ; Transient response ; Voltage ; Voltage control</subject><ispartof>IEEE transactions on industrial electronics (1982), 2022-12, Vol.69 (12), p.13849-13858</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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This necessitates an efficient control methodology to overcome the destabilization issue and regulate the response of the output voltage. In particular, this article proposes a novel interval type-III fuzzy neural network-based model predictive control (IT3FNNMPC) to mitigate the destructive effects of CPL in dc/dc boost converters implemented in the microgrid (MG) and power system distribution. In a typical MGs configuration, the IT3FNNMPC controller is formulated and designed in a constraint control problem to achieve a fast-transient response of system voltage. The feasibility and applicability of the designed IT3FNNMPC controller have been validated by hardware-in-the-loop real-time simulations.</description><subject>Control methods</subject><subject>Control systems</subject><subject>Control systems design</subject><subject>Controllers</subject><subject>DC power converters</subject><subject>Destabilization</subject><subject>Distributed generation</subject><subject>Electric potential</subject><subject>Electric power distribution</subject><subject>Electric power systems</subject><subject>Electronic devices</subject><subject>Fuzzy control</subject><subject>Fuzzy logic</subject><subject>Hardware-in-the-loop simulation</subject><subject>interval fuzzy type-III</subject><subject>model predictive control (MPC)</subject><subject>nonideal constant power loads (CPL)</subject><subject>Power converters</subject><subject>Power electronics</subject><subject>Power system stability</subject><subject>Predictive control</subject><subject>Pulse width modulation</subject><subject>Stability analysis</subject><subject>Transient response</subject><subject>Voltage</subject><subject>Voltage control</subject><issn>0278-0046</issn><issn>1557-9948</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kE1LAzEQhoMoWKt3wUvA89bJ5-4etbZaqFiwel1iMitb1qYmaaX99W5p8TDM5XnfYR5CrhkMGIPybj4ZDThwNhBMSFD8hPSYUnlWlrI4JT3geZEBSH1OLmJcADCpmOqR-sU7bOksoGtsajZIh36Zgm_pg4no6Hy7wkzQ8Xq329JRTM23ST7QupsP3ybzhfQtmc-mbXYmNX5JfU0fh3TmfzHsqzYYEoZ4Sc5q00a8Ou4-eR-P5sPnbPr6NBneTzPLS5Yy7Zix1mrHFToOUnADDvI6R4WSW4dc56bmxirnZKmZtCWAcVqgLiwTueiT20PvKvifNcZULfw6LLuTFddFkQMXSnYUHCgbfIwB62oVusfCtmJQ7W1Wnc1qb7M62uwiN4dIg4j_eKkVhxLEH-rXcLg</recordid><startdate>20221201</startdate><enddate>20221201</enddate><creator>Gheisarnejad, Meysam</creator><creator>Mohammadzadeh, Ardashir</creator><creator>Khooban, Mohammad-Hassan</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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This necessitates an efficient control methodology to overcome the destabilization issue and regulate the response of the output voltage. In particular, this article proposes a novel interval type-III fuzzy neural network-based model predictive control (IT3FNNMPC) to mitigate the destructive effects of CPL in dc/dc boost converters implemented in the microgrid (MG) and power system distribution. In a typical MGs configuration, the IT3FNNMPC controller is formulated and designed in a constraint control problem to achieve a fast-transient response of system voltage. The feasibility and applicability of the designed IT3FNNMPC controller have been validated by hardware-in-the-loop real-time simulations.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TIE.2021.3134052</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-5173-4563</orcidid><orcidid>https://orcid.org/0000-0001-7370-5106</orcidid><orcidid>https://orcid.org/0000-0003-0223-4081</orcidid></addata></record> |
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| ispartof | IEEE transactions on industrial electronics (1982), 2022-12, Vol.69 (12), p.13849-13858 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Control methods Control systems Control systems design Controllers DC power converters Destabilization Distributed generation Electric potential Electric power distribution Electric power systems Electronic devices Fuzzy control Fuzzy logic Hardware-in-the-loop simulation interval fuzzy type-III model predictive control (MPC) nonideal constant power loads (CPL) Power converters Power electronics Power system stability Predictive control Pulse width modulation Stability analysis Transient response Voltage Voltage control |
| title | Model Predictive Control Based Type-3 Fuzzy Estimator for Voltage Stabilization of DC Power Converters |
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