An Optimization Approach to State-Delay Identification
We consider a nonlinear delay-differential system with unknown state-delays. Our goal is to identify these state-delays using experimental data. To this end, we formulate a dynamic optimization problem in which the state-delays are decision variables and the cost function measures the discrepancy be...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
IEEE
2010
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| Online Access: | http://hdl.handle.net/20.500.11937/48419 |
| _version_ | 1848758103379542016 |
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| author | Loxton, Ryan Teo, Kok Lay Rehbock, Volker |
| author_facet | Loxton, Ryan Teo, Kok Lay Rehbock, Volker |
| author_sort | Loxton, Ryan |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | We consider a nonlinear delay-differential system with unknown state-delays. Our goal is to identify these state-delays using experimental data. To this end, we formulate a dynamic optimization problem in which the state-delays are decision variables and the cost function measures the discrepancy between predicted and observed system output. We then show that the gradient of this problem's cost function can be computed by solving an auxiliary delay-differential system. By exploiting this result, the state-delay identification problem can be solved efficiently using a gradient-based optimization method. |
| first_indexed | 2025-11-14T09:38:40Z |
| format | Journal Article |
| id | curtin-20.500.11937-48419 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:38:40Z |
| publishDate | 2010 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-484192017-09-13T16:01:42Z An Optimization Approach to State-Delay Identification Loxton, Ryan Teo, Kok Lay Rehbock, Volker optimization methods system identification nonlinear control systems Delay systems We consider a nonlinear delay-differential system with unknown state-delays. Our goal is to identify these state-delays using experimental data. To this end, we formulate a dynamic optimization problem in which the state-delays are decision variables and the cost function measures the discrepancy between predicted and observed system output. We then show that the gradient of this problem's cost function can be computed by solving an auxiliary delay-differential system. By exploiting this result, the state-delay identification problem can be solved efficiently using a gradient-based optimization method. 2010 Journal Article http://hdl.handle.net/20.500.11937/48419 10.1109/TAC.2010.2050710 IEEE fulltext |
| spellingShingle | optimization methods system identification nonlinear control systems Delay systems Loxton, Ryan Teo, Kok Lay Rehbock, Volker An Optimization Approach to State-Delay Identification |
| title | An Optimization Approach to State-Delay Identification |
| title_full | An Optimization Approach to State-Delay Identification |
| title_fullStr | An Optimization Approach to State-Delay Identification |
| title_full_unstemmed | An Optimization Approach to State-Delay Identification |
| title_short | An Optimization Approach to State-Delay Identification |
| title_sort | optimization approach to state-delay identification |
| topic | optimization methods system identification nonlinear control systems Delay systems |
| url | http://hdl.handle.net/20.500.11937/48419 |