Speed Estimation Using Extended Kalman Filter Technique
This paper presents a state estimation technique for speed senseless field oriented control of induction motors. The theoretical basis of each algorithm is explained in detail and its performance is tested with simulations using MATLAB package VER.6.3. A stochastical nonlinear state estimator, Exten...
| Автор: | |
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| Формат: | Стаття |
| Мова: | English |
| Опубліковано: |
Tikrit University
2005-08-01
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| Серія: | Tikrit Journal of Engineering Sciences |
| Предмети: | |
| Онлайн доступ: | https://tj-es.com/ojs/index.php/tjes/article/view/757 |
| _version_ | 1827903224033574912 |
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| author | Ayad Kasem Hussen |
| author_facet | Ayad Kasem Hussen |
| author_sort | Ayad Kasem Hussen |
| collection | DOAJ |
| description | This paper presents a state estimation technique for speed senseless field oriented control of induction motors. The theoretical basis of each algorithm is explained in detail and its performance is tested with simulations using MATLAB package VER.6.3. A stochastical nonlinear state estimator, Extended Kalman Filter (EKF) is presented. The motor model designed for EKF application involves rotor speed, dq-axis stator currents. Thus, using this observer the rotor speed and rotor fluxes are estimated simultaneously. Different from the widely accepted use of EKF, in which it is optimized for either steady- state or transient operations, here using adjustable noise level process algorithm the optimization of EKF has been done for both states; the steady-state and the transient-state of operations.
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| first_indexed | 2024-03-13T00:10:50Z |
| format | Article |
| id | doaj.art-a87b2bcdbf5241f0b4c85d38d93b56a0 |
| institution | Directory Open Access Journal |
| issn | 1813-162X 2312-7589 |
| language | English |
| last_indexed | 2024-03-13T00:10:50Z |
| publishDate | 2005-08-01 |
| publisher | Tikrit University |
| record_format | Article |
| series | Tikrit Journal of Engineering Sciences |
| spelling | doaj.art-a87b2bcdbf5241f0b4c85d38d93b56a02023-07-12T12:56:48ZengTikrit UniversityTikrit Journal of Engineering Sciences1813-162X2312-75892005-08-0112310.25130/tjes.12.3.06Speed Estimation Using Extended Kalman Filter TechniqueAyad Kasem Hussen0College of Electronic and Electrical Techniques, IraqThis paper presents a state estimation technique for speed senseless field oriented control of induction motors. The theoretical basis of each algorithm is explained in detail and its performance is tested with simulations using MATLAB package VER.6.3. A stochastical nonlinear state estimator, Extended Kalman Filter (EKF) is presented. The motor model designed for EKF application involves rotor speed, dq-axis stator currents. Thus, using this observer the rotor speed and rotor fluxes are estimated simultaneously. Different from the widely accepted use of EKF, in which it is optimized for either steady- state or transient operations, here using adjustable noise level process algorithm the optimization of EKF has been done for both states; the steady-state and the transient-state of operations. https://tj-es.com/ojs/index.php/tjes/article/view/757Induction motorKalman filterestimationsimulation |
| spellingShingle | Ayad Kasem Hussen Speed Estimation Using Extended Kalman Filter Technique Tikrit Journal of Engineering Sciences Induction motor Kalman filter estimation simulation |
| title | Speed Estimation Using Extended Kalman Filter Technique |
| title_full | Speed Estimation Using Extended Kalman Filter Technique |
| title_fullStr | Speed Estimation Using Extended Kalman Filter Technique |
| title_full_unstemmed | Speed Estimation Using Extended Kalman Filter Technique |
| title_short | Speed Estimation Using Extended Kalman Filter Technique |
| title_sort | speed estimation using extended kalman filter technique |
| topic | Induction motor Kalman filter estimation simulation |
| url | https://tj-es.com/ojs/index.php/tjes/article/view/757 |
| work_keys_str_mv | AT ayadkasemhussen speedestimationusingextendedkalmanfiltertechnique |