Parameter identification for systems with bounded disturbances
This thesis contains three parts. In the first part, a set-membership identification algorithm is developed for systems with bounded disturbances. Except an upper bound of the disturbances, the disturbances are totally unknown. The algorithm contains a variable non-negative weighting factor which is...
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sg-ntu-dr.10356-197032023-07-04T15:27:27Z Parameter identification for systems with bounded disturbances Tan, Guo Jie. Wen, Chan Gyun School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering This thesis contains three parts. In the first part, a set-membership identification algorithm is developed for systems with bounded disturbances. Except an upper bound of the disturbances, the disturbances are totally unknown. The algorithm contains a variable non-negative weighting factor which is selected according to whether the new observed data contains sufficient information. The proposed approach not only ensures that the estimation error is bounded and non-increasing, but also possesses some good inherent features for any bounded system input. Furthermore, it will be shown that, with persistent exciting input, the parameter estimate provided by the algorithm converges to a residual region, and its upper bound is also given. Master of Engineering 2009-12-14T06:22:38Z 2009-12-14T06:22:38Z 1996 1996 Thesis http://hdl.handle.net/10356/19703 en NANYANG TECHNOLOGICAL UNIVERSITY 141 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering Tan, Guo Jie. Parameter identification for systems with bounded disturbances |
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This thesis contains three parts. In the first part, a set-membership identification algorithm is developed for systems with bounded disturbances. Except an upper bound of the disturbances, the disturbances are totally unknown. The algorithm contains a variable non-negative weighting factor which is selected according to whether the new observed data contains sufficient information. The proposed approach not only ensures that the estimation error is bounded and non-increasing, but also possesses some good inherent features for any bounded system input. Furthermore, it will be shown that, with persistent exciting input, the parameter estimate provided by the algorithm converges to a residual region, and its upper bound is also given. |
author2 |
Wen, Chan Gyun |
author_facet |
Wen, Chan Gyun Tan, Guo Jie. |
format |
Theses and Dissertations |
author |
Tan, Guo Jie. |
author_sort |
Tan, Guo Jie. |
title |
Parameter identification for systems with bounded disturbances |
title_short |
Parameter identification for systems with bounded disturbances |
title_full |
Parameter identification for systems with bounded disturbances |
title_fullStr |
Parameter identification for systems with bounded disturbances |
title_full_unstemmed |
Parameter identification for systems with bounded disturbances |
title_sort |
parameter identification for systems with bounded disturbances |
publishDate |
2009 |
url |
http://hdl.handle.net/10356/19703 |
_version_ |
1772825344242352128 |