Intelligent estimation of uncertainty bounds of an active magnetic bearings using ANFIS
Active magnetic bearings is known to be inherently unstable systems that have a widespread applications and an increased potential research area in today’s technology. So far many controllers including H∞ robust controller has been developed for the system. However, proper selection of the requ...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/5387/ http://irep.iium.edu.my/5387/ http://irep.iium.edu.my/5387/ http://irep.iium.edu.my/5387/1/mass2011_safanah.pdf |
| Summary: | Active magnetic bearings is known to be
inherently unstable systems that have a widespread applications
and an increased potential research area in today’s technology.
So far many controllers including H∞ robust controller has been
developed for the system. However, proper selection of the
required weighting functions for robust and non-conservative
controller synthesize is still a critical issue that needs more
investigations. In this paper the selection of uncertainty
weighting function for the robust controller synthesize is
automated by intelligent estimation of uncertainty weighting
functions using adaptive neuro fuzzy inference system (ANFIS).
Then a robust H∞ controller for the magnetic bearings is designed based on the intelligent estimated uncertainty. v- gap metric is utilized to validate the estimated uncertainty bounds for improved robust stability. Comparison with another neural based estimation method of uncertainty proves the validity of the applied approach |
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