Two-vector Dimensionless Model Predictive Control of PMSM Drives Based on Fuzzy Decision Making
Model predictive controls (MPCs) with the merits of non-linear multi-variable control can achieve better performance than other commonly used control methods for permanent magnet synchronous motor (PMSM) drives. However, the conventional MPCs have various issues, including unsatisfactory steady-stat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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China Electrotechnical Society
2022-12-01
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| Series: | CES Transactions on Electrical Machines and Systems |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10004937 |
| _version_ | 1797755726584610816 |
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| author | Nabil Farah Gang Lei Jianguo Zhu Youguang Guo |
| author_facet | Nabil Farah Gang Lei Jianguo Zhu Youguang Guo |
| author_sort | Nabil Farah |
| collection | DOAJ |
| description | Model predictive controls (MPCs) with the merits of non-linear multi-variable control can achieve better performance than other commonly used control methods for permanent magnet synchronous motor (PMSM) drives. However, the conventional MPCs have various issues, including unsatisfactory steady-state performance, variable switching frequency, and difficult selection of appropriate weighting factors. This paper proposes two different improved MPC methods to deal with these issues. One method is the two-vector dimensionless model predictive torque control (MPTC). Two cost functions (torque and flux) and fuzzy decision-making are used to eliminate the weighting factor and select the first optimum vector. The torque cost function selects a second vector whose duty cycle is determined based on the torque error. The other method is the two-vector dimensionless model predictive current control (MPCC). The first vector is selected the same as in the conventional MPC method. Two separate current cost functions and fuzzy decision-making are used to select the second vector whose duty cycle is determined based on the current error. Both proposed methods utilize the space vector PWM modulator to regulate the switching frequency. Numerical simulation results show that the proposed methods have better steady-state and transient performances than the conventional MPCs and other existing improved MPCs. |
| first_indexed | 2024-03-12T17:50:21Z |
| format | Article |
| id | doaj.art-3645db31f88041f08b23cf17bd869d75 |
| institution | Directory Open Access Journal |
| issn | 2096-3564 2837-0325 |
| language | English |
| last_indexed | 2024-03-12T17:50:21Z |
| publishDate | 2022-12-01 |
| publisher | China Electrotechnical Society |
| record_format | Article |
| series | CES Transactions on Electrical Machines and Systems |
| spelling | doaj.art-3645db31f88041f08b23cf17bd869d752023-08-03T07:24:04ZengChina Electrotechnical SocietyCES Transactions on Electrical Machines and Systems2096-35642837-03252022-12-016439340310.30941/CESTEMS.2022.00051Two-vector Dimensionless Model Predictive Control of PMSM Drives Based on Fuzzy Decision MakingNabil Farah0Gang Lei1 Jianguo Zhu2Youguang Guo3School of Electrical and Data Engineering University of Technology Sydney (UTS), NSW, AustraliaSchool of Electrical and Data Engineering, University of Technology, Sydney, NSW, AustraliaSchool of Electrical and Information Engineering, University of Sydney, NSW, AustraliaSchool of Electrical and Data Engineering, University of Technology, Sydney, NSW, AustraliaModel predictive controls (MPCs) with the merits of non-linear multi-variable control can achieve better performance than other commonly used control methods for permanent magnet synchronous motor (PMSM) drives. However, the conventional MPCs have various issues, including unsatisfactory steady-state performance, variable switching frequency, and difficult selection of appropriate weighting factors. This paper proposes two different improved MPC methods to deal with these issues. One method is the two-vector dimensionless model predictive torque control (MPTC). Two cost functions (torque and flux) and fuzzy decision-making are used to eliminate the weighting factor and select the first optimum vector. The torque cost function selects a second vector whose duty cycle is determined based on the torque error. The other method is the two-vector dimensionless model predictive current control (MPCC). The first vector is selected the same as in the conventional MPC method. Two separate current cost functions and fuzzy decision-making are used to select the second vector whose duty cycle is determined based on the current error. Both proposed methods utilize the space vector PWM modulator to regulate the switching frequency. Numerical simulation results show that the proposed methods have better steady-state and transient performances than the conventional MPCs and other existing improved MPCs.https://ieeexplore.ieee.org/document/10004937electrical drivespermanent magnet synchronous motorsmodel predictive control |
| spellingShingle | Nabil Farah Gang Lei Jianguo Zhu Youguang Guo Two-vector Dimensionless Model Predictive Control of PMSM Drives Based on Fuzzy Decision Making CES Transactions on Electrical Machines and Systems electrical drives permanent magnet synchronous motors model predictive control |
| title | Two-vector Dimensionless Model Predictive Control of PMSM Drives Based on Fuzzy Decision Making |
| title_full | Two-vector Dimensionless Model Predictive Control of PMSM Drives Based on Fuzzy Decision Making |
| title_fullStr | Two-vector Dimensionless Model Predictive Control of PMSM Drives Based on Fuzzy Decision Making |
| title_full_unstemmed | Two-vector Dimensionless Model Predictive Control of PMSM Drives Based on Fuzzy Decision Making |
| title_short | Two-vector Dimensionless Model Predictive Control of PMSM Drives Based on Fuzzy Decision Making |
| title_sort | two vector dimensionless model predictive control of pmsm drives based on fuzzy decision making |
| topic | electrical drives permanent magnet synchronous motors model predictive control |
| url | https://ieeexplore.ieee.org/document/10004937 |
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