Estimation of parameters of a laboratory attitude control simulator using least squares method and hybrid intelligent optimization
In this paper, the parameters of the dynamic model of a three-degree-of-freedom simulator based on air bearing, including moment of inertia, center of mass, using experimental data in a maneuver in two ways: 1- hybrid optimization method of genetic algorithm and second-order programming and 2- The m...
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| Format: | Article |
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Semnan University
2022-06-01
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| Series: | مجله مدل سازی در مهندسی |
| Subjects: | |
| Online Access: | https://modelling.semnan.ac.ir/article_6058_c3550414aaac4069769f478a287ae950.pdf |
| _version_ | 1827342363459059712 |
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| author | Alireza Ahangrani Farahani Hamed Arefkhani Majid Hosseini amirhosseini tavakoli |
| author_facet | Alireza Ahangrani Farahani Hamed Arefkhani Majid Hosseini amirhosseini tavakoli |
| author_sort | Alireza Ahangrani Farahani |
| collection | DOAJ |
| description | In this paper, the parameters of the dynamic model of a three-degree-of-freedom simulator based on air bearing, including moment of inertia, center of mass, using experimental data in a maneuver in two ways: 1- hybrid optimization method of genetic algorithm and second-order programming and 2- The method of least squares error is estimated. To do this, a position maneuver is performed using reaction wheels, and torque values as well as angular velocities around three axes are recorded. The table parameters are then estimated using the stored data and the implementation of the two methods. The results show that with the least squares method, unlike the hybrid optimization algorithm, with a attitude control test from the non-zero initial point to the origin, it is not possible to derive a good estimate and different tests are needed to stimulate all system modes. While in the hybrid optimization method, by performing the same experiment, the desired results of the system estimation can be presented. To validate the implemented algorithm, the performance of the closed loop of the table in the laboratory environment and the simulated model were evaluated and compared, which indicates the appropriate accuracy (less than 5% error) of the estimation methods. |
| first_indexed | 2024-03-07T22:06:35Z |
| format | Article |
| id | doaj.art-db1b3ca0d70345e0b9ffcf7fc364f8de |
| institution | Directory Open Access Journal |
| issn | 2008-4854 2783-2538 |
| language | fas |
| last_indexed | 2024-03-07T22:06:35Z |
| publishDate | 2022-06-01 |
| publisher | Semnan University |
| record_format | Article |
| series | مجله مدل سازی در مهندسی |
| spelling | doaj.art-db1b3ca0d70345e0b9ffcf7fc364f8de2024-02-23T19:09:30ZfasSemnan Universityمجله مدل سازی در مهندسی2008-48542783-25382022-06-012069293910.22075/jme.2022.25020.21666058Estimation of parameters of a laboratory attitude control simulator using least squares method and hybrid intelligent optimizationAlireza Ahangrani Farahani0Hamed Arefkhani1Majid Hosseini2amirhosseini tavakoli3Researcher, Faculty of Aerospace engineering, Malek Ashtar University of TechnologyResearcher, Faculty of Aerospace engineering, Malek Ashtar University of Technology, tehran, iranFaculty of aerospace engineering, malek e ashtar univercity of technology, tehran, iranResearch assistant, Faculty of Aerospace engineering, Malek Ashtar University of Technology, tehran, iranIn this paper, the parameters of the dynamic model of a three-degree-of-freedom simulator based on air bearing, including moment of inertia, center of mass, using experimental data in a maneuver in two ways: 1- hybrid optimization method of genetic algorithm and second-order programming and 2- The method of least squares error is estimated. To do this, a position maneuver is performed using reaction wheels, and torque values as well as angular velocities around three axes are recorded. The table parameters are then estimated using the stored data and the implementation of the two methods. The results show that with the least squares method, unlike the hybrid optimization algorithm, with a attitude control test from the non-zero initial point to the origin, it is not possible to derive a good estimate and different tests are needed to stimulate all system modes. While in the hybrid optimization method, by performing the same experiment, the desired results of the system estimation can be presented. To validate the implemented algorithm, the performance of the closed loop of the table in the laboratory environment and the simulated model were evaluated and compared, which indicates the appropriate accuracy (less than 5% error) of the estimation methods.https://modelling.semnan.ac.ir/article_6058_c3550414aaac4069769f478a287ae950.pdfattitude determination and control simulatorparameter estimationleast squares error algorithmhybrid optimization algorithm |
| spellingShingle | Alireza Ahangrani Farahani Hamed Arefkhani Majid Hosseini amirhosseini tavakoli Estimation of parameters of a laboratory attitude control simulator using least squares method and hybrid intelligent optimization مجله مدل سازی در مهندسی attitude determination and control simulator parameter estimation least squares error algorithm hybrid optimization algorithm |
| title | Estimation of parameters of a laboratory attitude control simulator using least squares method and hybrid intelligent optimization |
| title_full | Estimation of parameters of a laboratory attitude control simulator using least squares method and hybrid intelligent optimization |
| title_fullStr | Estimation of parameters of a laboratory attitude control simulator using least squares method and hybrid intelligent optimization |
| title_full_unstemmed | Estimation of parameters of a laboratory attitude control simulator using least squares method and hybrid intelligent optimization |
| title_short | Estimation of parameters of a laboratory attitude control simulator using least squares method and hybrid intelligent optimization |
| title_sort | estimation of parameters of a laboratory attitude control simulator using least squares method and hybrid intelligent optimization |
| topic | attitude determination and control simulator parameter estimation least squares error algorithm hybrid optimization algorithm |
| url | https://modelling.semnan.ac.ir/article_6058_c3550414aaac4069769f478a287ae950.pdf |
| work_keys_str_mv | AT alirezaahangranifarahani estimationofparametersofalaboratoryattitudecontrolsimulatorusingleastsquaresmethodandhybridintelligentoptimization AT hamedarefkhani estimationofparametersofalaboratoryattitudecontrolsimulatorusingleastsquaresmethodandhybridintelligentoptimization AT majidhosseini estimationofparametersofalaboratoryattitudecontrolsimulatorusingleastsquaresmethodandhybridintelligentoptimization AT amirhosseinitavakoli estimationofparametersofalaboratoryattitudecontrolsimulatorusingleastsquaresmethodandhybridintelligentoptimization |