Comparative study of parametric and intelligent unstructured uncertainties for robust controller design

This paper describes the design, analysis and comparison of two ∞ H controllers that use two different uncertainty model representations; unstructured and structured (parametric) uncertainties. The later is usually considered as less conservative. However, the application of intelligent techniques...

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Main Authors: M. Raafat, Safanah, Martono, Wahyudi, Akmeliawati, Rini
Format: Proceeding Paper
Language:English
Published: 2009
Subjects:
Online Access:http://irep.iium.edu.my/5396/
http://irep.iium.edu.my/5396/1/isiea2009_safanah.pdf
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author M. Raafat, Safanah
Martono, Wahyudi
Akmeliawati, Rini
author_facet M. Raafat, Safanah
Martono, Wahyudi
Akmeliawati, Rini
author_sort M. Raafat, Safanah
building IIUM Repository
collection Online Access
description This paper describes the design, analysis and comparison of two ∞ H controllers that use two different uncertainty model representations; unstructured and structured (parametric) uncertainties. The later is usually considered as less conservative. However, the application of intelligent techniques like Adaptive Neural Fuzzy Inference System (ANFIS) in the identification of unstructured uncertainty bounds provides considerable improvements in reduction of conservatism and guaranteed robust stability and performance, as illustrated in the results of practical implementation to a servo motion system .
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format Proceeding Paper
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institution International Islamic University Malaysia
institution_category Local University
language English
last_indexed 2025-11-14T14:31:00Z
publishDate 2009
recordtype eprints
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spelling iium-53962012-05-11T18:45:49Z http://irep.iium.edu.my/5396/ Comparative study of parametric and intelligent unstructured uncertainties for robust controller design M. Raafat, Safanah Martono, Wahyudi Akmeliawati, Rini TJ212 Control engineering This paper describes the design, analysis and comparison of two ∞ H controllers that use two different uncertainty model representations; unstructured and structured (parametric) uncertainties. The later is usually considered as less conservative. However, the application of intelligent techniques like Adaptive Neural Fuzzy Inference System (ANFIS) in the identification of unstructured uncertainty bounds provides considerable improvements in reduction of conservatism and guaranteed robust stability and performance, as illustrated in the results of practical implementation to a servo motion system . 2009 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/5396/1/isiea2009_safanah.pdf M. Raafat, Safanah and Martono, Wahyudi and Akmeliawati, Rini (2009) Comparative study of parametric and intelligent unstructured uncertainties for robust controller design. In: 2009 IEEE Symposium on Industrial Electronics and Applications (ISIEA 2009, 4- 6, October, 2009, Kuala Lumpur, Malaysia. http://dx.doi.org/10.1109/ISIEA.2009.5356444 doi:10.1109/ISIEA.2009.5356444
spellingShingle TJ212 Control engineering
M. Raafat, Safanah
Martono, Wahyudi
Akmeliawati, Rini
Comparative study of parametric and intelligent unstructured uncertainties for robust controller design
title Comparative study of parametric and intelligent unstructured uncertainties for robust controller design
title_full Comparative study of parametric and intelligent unstructured uncertainties for robust controller design
title_fullStr Comparative study of parametric and intelligent unstructured uncertainties for robust controller design
title_full_unstemmed Comparative study of parametric and intelligent unstructured uncertainties for robust controller design
title_short Comparative study of parametric and intelligent unstructured uncertainties for robust controller design
title_sort comparative study of parametric and intelligent unstructured uncertainties for robust controller design
topic TJ212 Control engineering
url http://irep.iium.edu.my/5396/
http://irep.iium.edu.my/5396/
http://irep.iium.edu.my/5396/
http://irep.iium.edu.my/5396/1/isiea2009_safanah.pdf