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: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2009
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/5396/1/isiea2009_safanah.pdf http://irep.iium.edu.my/5396/ http://dx.doi.org/10.1109/ISIEA.2009.5356444 |
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| Summary: | 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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