Intelligent identification of uncertainty bounds for robust servo controlled system

In this paper a new intelligent identification method of uncertainty bound utilizes an adaptive neurofuzzy inference system (ANFIS) in a feedback scheme isnproposed. The proposed ANFIS feedback structurenperforms better in determining the uncertainty bounds withnminimum number of iterations and erro...

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Main Authors: M. Raafat, Safanah, Akmeliawati, Rini, Martono, Wahyudi
Format: Proceeding Paper
Language:English
Published: 2010
Subjects:
Online Access:http://irep.iium.edu.my/5385/
http://irep.iium.edu.my/5385/1/iccaie2010_safanah.pdf
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author M. Raafat, Safanah
Akmeliawati, Rini
Martono, Wahyudi
author_facet M. Raafat, Safanah
Akmeliawati, Rini
Martono, Wahyudi
author_sort M. Raafat, Safanah
building IIUM Repository
collection Online Access
description In this paper a new intelligent identification method of uncertainty bound utilizes an adaptive neurofuzzy inference system (ANFIS) in a feedback scheme isnproposed. The proposed ANFIS feedback structurenperforms better in determining the uncertainty bounds withnminimum number of iterations and error. In our proposedntechnique, the intelligent identified uncertainty weightingnfunction is validated utilizing v-gap to ensure the stability of the designed H� controlled system. Our proposed intelligent identification of uncertainty bound is demonstrated on a servo motion system. Simulation and experimental results show that the new ANFIS identifier is more reliable and highly efficient in estimating the best uncertainty weightingnfunction for robust controller design
first_indexed 2025-11-14T14:30:58Z
format Proceeding Paper
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institution International Islamic University Malaysia
institution_category Local University
language English
last_indexed 2025-11-14T14:30:58Z
publishDate 2010
recordtype eprints
repository_type Digital Repository
spelling iium-53852012-01-25T00:19:23Z http://irep.iium.edu.my/5385/ Intelligent identification of uncertainty bounds for robust servo controlled system M. Raafat, Safanah Akmeliawati, Rini Martono, Wahyudi TJ212 Control engineering In this paper a new intelligent identification method of uncertainty bound utilizes an adaptive neurofuzzy inference system (ANFIS) in a feedback scheme isnproposed. The proposed ANFIS feedback structurenperforms better in determining the uncertainty bounds withnminimum number of iterations and error. In our proposedntechnique, the intelligent identified uncertainty weightingnfunction is validated utilizing v-gap to ensure the stability of the designed H� controlled system. Our proposed intelligent identification of uncertainty bound is demonstrated on a servo motion system. Simulation and experimental results show that the new ANFIS identifier is more reliable and highly efficient in estimating the best uncertainty weightingnfunction for robust controller design 2010 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/5385/1/iccaie2010_safanah.pdf M. Raafat, Safanah and Akmeliawati, Rini and Martono, Wahyudi (2010) Intelligent identification of uncertainty bounds for robust servo controlled system. In: 2010 International Conference on Computer Applications and Industrial Electronics (ICCAIE 2010), December 5-7, 2010, Kuala Lumpur, Malaysia, 5-7 Dec., 2010, Kuala Lumpur. http://dx.doi.org/10.1109/ICCAIE.2010.5735144 doi:10.1109/ICCAIE.2010.5735144
spellingShingle TJ212 Control engineering
M. Raafat, Safanah
Akmeliawati, Rini
Martono, Wahyudi
Intelligent identification of uncertainty bounds for robust servo controlled system
title Intelligent identification of uncertainty bounds for robust servo controlled system
title_full Intelligent identification of uncertainty bounds for robust servo controlled system
title_fullStr Intelligent identification of uncertainty bounds for robust servo controlled system
title_full_unstemmed Intelligent identification of uncertainty bounds for robust servo controlled system
title_short Intelligent identification of uncertainty bounds for robust servo controlled system
title_sort intelligent identification of uncertainty bounds for robust servo controlled system
topic TJ212 Control engineering
url http://irep.iium.edu.my/5385/
http://irep.iium.edu.my/5385/
http://irep.iium.edu.my/5385/
http://irep.iium.edu.my/5385/1/iccaie2010_safanah.pdf