Sliding Mode Observer with Adaptive Parameter Estimation for Sensorless Control of IPMSM
To improve the observation accuracy and robustness of the sensorless control of an interior permanent magnet synchronous motor (IPMSM), a sliding mode observer based on the super twisting algorithm (STA-SMO) with adaptive parameters estimation control is proposed, as parameter mismatches are conside...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/22/5991 |
| _version_ | 1797547690662297600 |
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| author | Yubo Liu Junlong Fang Kezhu Tan Boyan Huang Wenshuai He |
| author_facet | Yubo Liu Junlong Fang Kezhu Tan Boyan Huang Wenshuai He |
| author_sort | Yubo Liu |
| collection | DOAJ |
| description | To improve the observation accuracy and robustness of the sensorless control of an interior permanent magnet synchronous motor (IPMSM), a sliding mode observer based on the super twisting algorithm (STA-SMO) with adaptive parameters estimation control is proposed, as parameter mismatches are considered. First, the conventional sliding mode observer (CSMO) is analyzed. The conventional exponential approach law produces a large chattering phenomenon in the back EMF estimation, which causes a large observation error when filtering the chattering through the low-pass filter. Second, a high-order approach law of the super twisting algorithm is introduced to observe the rotor position and speed estimation, which uses the integral function to eliminate the chattering of the sliding mode. Third, an adaptive parameter estimation control (APEC) is presented to enhance the observation accuracy caused by parameter mismatches; the motor parameter adaptive law of the APEC is designed by Lyapunov’s stability law. Finally, the proposed method not only reduces both the chattering and the low-pass filter, but it also enhances accuracy and robustness against parameter mismatches, as discussed through simulations and experiments. |
| first_indexed | 2024-03-10T14:47:41Z |
| format | Article |
| id | doaj.art-564614fc92b349ef818715ebc7a2307b |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T14:47:41Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-564614fc92b349ef818715ebc7a2307b2023-11-20T21:11:43ZengMDPI AGEnergies1996-10732020-11-011322599110.3390/en13225991Sliding Mode Observer with Adaptive Parameter Estimation for Sensorless Control of IPMSMYubo Liu0Junlong Fang1Kezhu Tan2Boyan Huang3Wenshuai He4College of Electrical and Information, Northeast Agricultural University, Harbin 150030, ChinaCollege of Electrical and Information, Northeast Agricultural University, Harbin 150030, ChinaCollege of Electrical and Information, Northeast Agricultural University, Harbin 150030, ChinaCollege of Electrical and Information, Northeast Agricultural University, Harbin 150030, ChinaCollege of Electrical and Information, Northeast Agricultural University, Harbin 150030, ChinaTo improve the observation accuracy and robustness of the sensorless control of an interior permanent magnet synchronous motor (IPMSM), a sliding mode observer based on the super twisting algorithm (STA-SMO) with adaptive parameters estimation control is proposed, as parameter mismatches are considered. First, the conventional sliding mode observer (CSMO) is analyzed. The conventional exponential approach law produces a large chattering phenomenon in the back EMF estimation, which causes a large observation error when filtering the chattering through the low-pass filter. Second, a high-order approach law of the super twisting algorithm is introduced to observe the rotor position and speed estimation, which uses the integral function to eliminate the chattering of the sliding mode. Third, an adaptive parameter estimation control (APEC) is presented to enhance the observation accuracy caused by parameter mismatches; the motor parameter adaptive law of the APEC is designed by Lyapunov’s stability law. Finally, the proposed method not only reduces both the chattering and the low-pass filter, but it also enhances accuracy and robustness against parameter mismatches, as discussed through simulations and experiments.https://www.mdpi.com/1996-1073/13/22/5991interior permanent magnet synchronous motorsliding mode observersuper twisting algorithmadaptive parameters estimation controlparameter mismatch |
| spellingShingle | Yubo Liu Junlong Fang Kezhu Tan Boyan Huang Wenshuai He Sliding Mode Observer with Adaptive Parameter Estimation for Sensorless Control of IPMSM Energies interior permanent magnet synchronous motor sliding mode observer super twisting algorithm adaptive parameters estimation control parameter mismatch |
| title | Sliding Mode Observer with Adaptive Parameter Estimation for Sensorless Control of IPMSM |
| title_full | Sliding Mode Observer with Adaptive Parameter Estimation for Sensorless Control of IPMSM |
| title_fullStr | Sliding Mode Observer with Adaptive Parameter Estimation for Sensorless Control of IPMSM |
| title_full_unstemmed | Sliding Mode Observer with Adaptive Parameter Estimation for Sensorless Control of IPMSM |
| title_short | Sliding Mode Observer with Adaptive Parameter Estimation for Sensorless Control of IPMSM |
| title_sort | sliding mode observer with adaptive parameter estimation for sensorless control of ipmsm |
| topic | interior permanent magnet synchronous motor sliding mode observer super twisting algorithm adaptive parameters estimation control parameter mismatch |
| url | https://www.mdpi.com/1996-1073/13/22/5991 |
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