- Title
- On the optimality of open and closed loop experiments in system identification
- Creator
- Aguero, Juan C.; Goodwin, Graham C.
- Relation
- 45th IEEE Conference on Decision and Control 2006. Proceedings of the 45th IEEE Conference on Decison and Control 2006 (San Diego, CA 13-15 December, 2006 ) p. 163-168
- Relation
- http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4177773
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Resource Type
- conference paper
- Date
- 2006
- Description
- In this paper we analyse the strong optimality of open and closed loop experiments. In particular, we establish that when there is a constraint on the system input, then open loop experiments are optimal for a wide class of design criteria. Conversely, we show that when there is a constraint on the output power, then closed loop experiments are optimal for a class of systems and for a wide class of design criteria. Our analysis uses the non-asymptotic (in model order) variance expressions for dynamic systems.
- Subject
- closed loop experiment; dynamic systems; nonasymptotic variance expression; open loop experiment; optimality; system identification
- Identifier
- uon:2157
- Identifier
- http://hdl.handle.net/1959.13/28627
- Identifier
- ISBN:1424401712
- Rights
- Copyright © 2006 IEEE. Reprinted from the 45th IEEE Conference on Decision and Control 2006, p. 163-168. 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.
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