Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/28627
- On the optimality of open and closed loop experiments in system identification
Aguero, Juan C.;
Goodwin, Graham C.
- 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.
- 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
- Institute of Electrical and Electronics Engineers (IEEE)
closed loop experiment;
nonasymptotic variance expression;
open loop experiment;
- Resource Type
- conference paper
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