Title:
Adaptive Time Horizon Optimization in Model Predictive Control
Adaptive Time Horizon Optimization in Model Predictive Control
| dc.contributor.author | Droge, Greg | en_US |
| dc.contributor.author | Egerstedt, Magnus B. | en_US |
| dc.contributor.corporatename | Georgia Institute of Technology. Center for Robotics and Intelligent Machines | en_US |
| dc.contributor.corporatename | Georgia Institute of Technology. School of Electrical and Computer Engineering | en_US |
| dc.date.accessioned | 2011-09-30T17:30:14Z | |
| dc.date.available | 2011-09-30T17:30:14Z | |
| dc.date.issued | 2011-06 | |
| dc.description | © 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. | en_US |
| dc.description | Presented at the American Control Conference, San Francisco, CA, June 2011. | en_US |
| dc.description.abstract | Whenever the control task involves the tracking of a reference signal the performance is typically improved if one knows the future behavior of this reference. However in many applications this is typically not the case e.g. when the reference signal is generated by a human operator and a remedy to this can be to try and model the reference signal over a short time horizon. In this paper we address the problem of selecting this horizon in an adaptive fashion by minimizing a cost that takes into account the performance of the underlying control problem (that prefers longer time horizons) and the effectiveness of the reference signal model (that prefers shorter time horizons). The result is an adaptive time horizon controller that operates in a manner reminiscent of Model Predictive Control (MPC). | en_US |
| dc.identifier.citation | G. Droge and M. Egerstedt. Adaptive Time Horizon Optimization in Model Predictive Control. American Control Conference, San Francisco, CA, June 2011. | en_US |
| dc.identifier.isbn | 978-1-4577-0080-4 | |
| dc.identifier.issn | 0743-1619 | |
| dc.identifier.uri | http://hdl.handle.net/1853/41703 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Georgia Institute of Technology | en_US |
| dc.publisher.original | Institute of Electrical and Electronics Engineers | en_US |
| dc.subject | Adaptive control | en_US |
| dc.subject | Adaptive time horizon controller | en_US |
| dc.subject | Current measurement | en_US |
| dc.subject | Linear systems | en_US |
| dc.subject | Optimal control | en_US |
| dc.title | Adaptive Time Horizon Optimization in Model Predictive Control | en_US |
| dc.type | Text | |
| dc.type.genre | Proceedings | |
| dc.type.genre | Post-print | |
| dspace.entity.type | Publication | |
| local.contributor.author | Egerstedt, Magnus B. | |
| local.contributor.corporatename | School of Electrical and Computer Engineering | |
| local.contributor.corporatename | College of Engineering | |
| relation.isAuthorOfPublication | dd4872d3-2e0d-435d-861d-a61559d2bcb6 | |
| relation.isOrgUnitOfPublication | 5b7adef2-447c-4270-b9fc-846bd76f80f2 | |
| relation.isOrgUnitOfPublication | 7c022d60-21d5-497c-b552-95e489a06569 |
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