Editing System identification (section)

===Optimal design of experiments===
{{Main|Optimal design#System identification and stochastic approximation}}
The quality of system identification depends on the quality of the inputs, which are under the control of the systems engineer. Therefore, systems engineers have long used the principles of the [[design of experiments]].<ref>Spall, J. C. (2010), "Factorial Design for Efficient Experimentation: Generating Informative Data for System Identification," ''IEEE Control Systems Magazine'', vol. 30(5), pp. 38–53. https://doi.org/10.1109/MCS.2010.937677</ref> In recent decades, engineers have increasingly used the theory of [[optimal design|optimal experimental design]] to specify inputs that yield [[efficient estimator|maximally precise]] [[estimator]]s.<ref>{{cite book|title=Dynamic System Identification: Experiment Design and Data Analysis|last1=Goodwin|first1=Graham C.|last2=Payne|first2=Robert L.|publisher=Academic Press|year=1977|isbn=978-0-12-289750-4|name-list-style=amp}}</ref><ref>{{cite book|title=Identification of Parametric Models from Experimental Data|last1=Walter|first1=Éric|last2=Pronzato|first2=Luc|publisher=Springer|year=1997|name-list-style=amp}}
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