Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/38963
- Title
- On gradient-based search for multivariable system estimates
- Author/Creator
-
Wills, Adrian;
Ninness, Brett
- Institution
- The University of Newcastle. Faculty of Engineering & Built Environment, School of Electrical Engineering and Computer Science
- Description
- This paper addresses the design of gradient-based search algorithms for multivariable system estimation. In particular, the paper here considers so-called ldquofull parametrizationrdquo approaches, and establishes that the recently developed ldquodata-driven local coordinaterdquo methods can be seen as a special case within a broader class of techniques that are designed to deal with rank-deficient Jacobians. This informs the design of a new algorithm that, via a strategy of dynamic Jacobian rank determination, is illustrated to offer enhanced performance.
- Relation
- IEEE Transactions on Automatic Control Vol. 53, Issue 1, p. 298-306
- Publisher Link
- http://dx.doi.org/10.1109/TAC.2007.914953
- Date
- 2008
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Keyword(s)
-
gradient-based search (GBS);
parameter estimation;
system identification
- Resource Type
- journal article
- Rights
- Copyright © 2008 IEEE. Reprinted from IEEE Transactions on Automatic Control. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Newcastle's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
- Identifier
- http://hdl.handle.net/1959.13/38963
- Identifier
- ISSN:0018-9286
- Reviewed
- Full Text
-
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