Sliding mode control for permanent magnet synchronous motor of sensor-less considering time-varying disturbance
To solve the degradation in control performance of permanent magnet synchronous motors (PMSMs) due to uncertainties from parameter perturbation, as well as the problems arising from the speed sensor, such as high cost, demanding environmental requirements and deficient accuracy of estimation, this p...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Electric Drive for Locomotives
2023-01-01
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| Series: | 机车电传动 |
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| Online Access: | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2023.01.012 |
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| author | LI Xiangfei LIU Junqin WANG Jian ZHAO Kaihui YIN Yang ZOU Lihua |
| author_facet | LI Xiangfei LIU Junqin WANG Jian ZHAO Kaihui YIN Yang ZOU Lihua |
| author_sort | LI Xiangfei |
| collection | DOAJ |
| description | To solve the degradation in control performance of permanent magnet synchronous motors (PMSMs) due to uncertainties from parameter perturbation, as well as the problems arising from the speed sensor, such as high cost, demanding environmental requirements and deficient accuracy of estimation, this paper proposed an adaptive non-singular fast terminal sliding mode control strategy for PMSMs of sensor-less speed regulation based on the adaptive square root generalized high-order cubature Kalman filter (ASRGHCKF) algorithm. A mathematical model of PMSM was first established under parameter perturbation, and an adaptive non-singular fast terminal sliding mode control algorithm (ANFTSMC) was designed depending on the extended sliding mode disturbance observer (ESMDO). A novel exponential reaching law was selected to adaptively adjust the approach speed depending on the distance of the system from the sliding surface while the unknown disturbance of the system was accurately observed by ESMDO in real time. Finally, the speed and rotor position of the motor were estimated accurately, in combination with ASRGHCKF. Based on the simulation and semi-physical experiment results in comparison with PI control and the traditional sliding mode control (SMC) algorithm, the strategy under the current study was proven with better transient stability performance under motor parameter perturbation, benefiting to improving the sensor-less control effect of PMSM. |
| format | Article |
| id | doaj-art-9acfd7f039ba4a95aa29a050377b2aef |
| institution | OA Journals |
| issn | 1000-128X |
| language | zho |
| publishDate | 2023-01-01 |
| publisher | Editorial Department of Electric Drive for Locomotives |
| record_format | Article |
| series | 机车电传动 |
| spelling | doaj-art-9acfd7f039ba4a95aa29a050377b2aef2025-08-20T01:51:11ZzhoEditorial Department of Electric Drive for Locomotives机车电传动1000-128X2023-01-01869635729382Sliding mode control for permanent magnet synchronous motor of sensor-less considering time-varying disturbanceLI XiangfeiLIU JunqinWANG JianZHAO KaihuiYIN YangZOU LihuaTo solve the degradation in control performance of permanent magnet synchronous motors (PMSMs) due to uncertainties from parameter perturbation, as well as the problems arising from the speed sensor, such as high cost, demanding environmental requirements and deficient accuracy of estimation, this paper proposed an adaptive non-singular fast terminal sliding mode control strategy for PMSMs of sensor-less speed regulation based on the adaptive square root generalized high-order cubature Kalman filter (ASRGHCKF) algorithm. A mathematical model of PMSM was first established under parameter perturbation, and an adaptive non-singular fast terminal sliding mode control algorithm (ANFTSMC) was designed depending on the extended sliding mode disturbance observer (ESMDO). A novel exponential reaching law was selected to adaptively adjust the approach speed depending on the distance of the system from the sliding surface while the unknown disturbance of the system was accurately observed by ESMDO in real time. Finally, the speed and rotor position of the motor were estimated accurately, in combination with ASRGHCKF. Based on the simulation and semi-physical experiment results in comparison with PI control and the traditional sliding mode control (SMC) algorithm, the strategy under the current study was proven with better transient stability performance under motor parameter perturbation, benefiting to improving the sensor-less control effect of PMSM.http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2023.01.012permanent magnet synchronous motoradaptive generalized high order square root cubature Kalman-filter algorithmnon-singular fast terminal sliding modeextended sliding mode disturbance observer |
| spellingShingle | LI Xiangfei LIU Junqin WANG Jian ZHAO Kaihui YIN Yang ZOU Lihua Sliding mode control for permanent magnet synchronous motor of sensor-less considering time-varying disturbance 机车电传动 permanent magnet synchronous motor adaptive generalized high order square root cubature Kalman-filter algorithm non-singular fast terminal sliding mode extended sliding mode disturbance observer |
| title | Sliding mode control for permanent magnet synchronous motor of sensor-less considering time-varying disturbance |
| title_full | Sliding mode control for permanent magnet synchronous motor of sensor-less considering time-varying disturbance |
| title_fullStr | Sliding mode control for permanent magnet synchronous motor of sensor-less considering time-varying disturbance |
| title_full_unstemmed | Sliding mode control for permanent magnet synchronous motor of sensor-less considering time-varying disturbance |
| title_short | Sliding mode control for permanent magnet synchronous motor of sensor-less considering time-varying disturbance |
| title_sort | sliding mode control for permanent magnet synchronous motor of sensor less considering time varying disturbance |
| topic | permanent magnet synchronous motor adaptive generalized high order square root cubature Kalman-filter algorithm non-singular fast terminal sliding mode extended sliding mode disturbance observer |
| url | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2023.01.012 |
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