Robust identification of a single axis high precision positioning system
Robust control has been studied in recent years as an efficient methodology for the design of highly performing controllers of positioning systems. However, it is necessary to provide accurate nominal model and associated uncertainty bounds to design this type of controllers. The aim of this paper i...
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2009
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my.iium.irep.53702011-11-22T06:10:29Z http://irep.iium.edu.my/5370/ Robust identification of a single axis high precision positioning system Raafat, Safanah M. Martono, Wahyudi Akmeliawati, Rini Legowo, Ari TJ212 Control engineering Robust control has been studied in recent years as an efficient methodology for the design of highly performing controllers of positioning systems. However, it is necessary to provide accurate nominal model and associated uncertainty bounds to design this type of controllers. The aim of this paper is to robustly identify a single axis high precision positioning system with uncertainties. For a given data set a nominal model is identified then model error modeling techniques are used to handle uncertainties in modeling. To examine the quality of the identified nominal and modeling error models Hinfin is designed based on the identified uncertainties. Computer simulation and experimenting with the high precision positioning system verify that the obtained nominal model and modeling error model are reliable and the implemented approach can be used to develop an integrated identification and robust controller. 2009 Conference or Workshop Item REM application/pdf en http://irep.iium.edu.my/5370/1/cspa2009_safanah.pdf Raafat, Safanah M. and Martono, Wahyudi and Akmeliawati, Rini and Legowo, Ari (2009) Robust identification of a single axis high precision positioning system. In: 5th International Colloquium on Signal Processing & Its Applications, 2009. CSPA 2009. , 6-8 March 2009, Kuala Lumpur, Malaysia. http://dx.doi.org/10.1109/CSPA.2009.5069192 doi:10.1109/CSPA.2009.5069192 |
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English |
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TJ212 Control engineering |
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TJ212 Control engineering Raafat, Safanah M. Martono, Wahyudi Akmeliawati, Rini Legowo, Ari Robust identification of a single axis high precision positioning system |
| description |
Robust control has been studied in recent years as an efficient methodology for the design of highly performing controllers of positioning systems. However, it is necessary to provide accurate nominal model and associated uncertainty bounds to design this type of controllers. The aim of this paper is to robustly identify a single axis high precision positioning system with uncertainties. For a given data set a nominal model is identified then model error modeling techniques are used to handle uncertainties in modeling. To examine the quality of the identified nominal and modeling error models Hinfin is designed based on the identified uncertainties. Computer simulation and experimenting with the high precision positioning system verify that the obtained nominal model and modeling error model are reliable and the implemented approach can be used to develop an integrated identification and robust controller. |
| format |
Conference or Workshop Item |
| author |
Raafat, Safanah M. Martono, Wahyudi Akmeliawati, Rini Legowo, Ari |
| author_facet |
Raafat, Safanah M. Martono, Wahyudi Akmeliawati, Rini Legowo, Ari |
| author_sort |
Raafat, Safanah M. |
| title |
Robust identification of a single axis high precision positioning system |
| title_short |
Robust identification of a single axis high precision positioning system |
| title_full |
Robust identification of a single axis high precision positioning system |
| title_fullStr |
Robust identification of a single axis high precision positioning system |
| title_full_unstemmed |
Robust identification of a single axis high precision positioning system |
| title_sort |
robust identification of a single axis high precision positioning system |
| publishDate |
2009 |
| url |
http://irep.iium.edu.my/5370/1/cspa2009_safanah.pdf http://irep.iium.edu.my/5370/ http://dx.doi.org/10.1109/CSPA.2009.5069192 |
| _version_ |
1643605524869021696 |
| score |
13.251813 |