Variable Input Space Observer for Structural Health Monitoring of High-Rate Systems Hong, Jonathan Laflamme, Simon Laflamme, Simon Dodson, Jacob 2018-02-17T22:01:19.000 2020-06-30T06:54:07Z 2020-06-30T06:54:07Z 2016-01-01
dc.description.abstract <p>Some engineering systems experiencing high-rate dynamic events, including air bags, debris detection, and active blast protection systems, could benefit from high-rate real-time observers for enhanced performance. However, the task of high-rate state estimation is challenging, in particular for real-time applications where the rate of the observer’s convergence needs to be in the microsecond range. This paper discusses critical challenges in designing highrate observers, and argues that adaptive observers are promising at the task of state estimation, and that they could be applied at high-rates provided the development of strategies to substantially increase their convergence. A novel adaptive observer termed a variable input observer (VIO) is studied for its performance and its application for fault detection. The VIO is designed with an adaptive input space, where the hyperspace and coefficients of the state estimation function can change based on the complexity of the dynamic input. Results show good convergence of the VIO versus fixed input strategies.</p>
dc.format.mimetype application/pdf
dc.identifier archive/
dc.identifier.articleid 4845
dc.identifier.contextkey 9060686
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath qnde/2016/abstracts/308
dc.language.iso en
dc.relation.ispartofseries Review of Progress in Quantitative Nondestructive Evaluation
dc.source.bitstream archive/|||Fri Jan 14 23:29:28 UTC 2022
dc.subject.disciplines Structural Engineering
dc.subject.disciplines Structures and Materials
dc.subject.disciplines Systems and Communications
dc.title Variable Input Space Observer for Structural Health Monitoring of High-Rate Systems
dc.type event
dc.type.genre event
dspace.entity.type Publication
relation.isAuthorOfPublication 84547f08-8710-4934-b91e-ba5f46ab9abe
relation.isSeriesOfPublication 289a28b5-887e-4ddb-8c51-a88d07ebc3f3
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