Randomized Controls for Linear Plants and Confidence Regions for Parameters under External Arbitrary Noise

K. Amelin, O. Granichin

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8 Scopus citations


This paper considers the possibilities of randomized controls for designing confidence regions for unknown parameters. The assumptions about external noise that affect a linear plant are reduced to a minimum: external noise can virtually be arbitrary, but, independently of it, the user must be able to add test perturbations through the input channel. Based on a finite set of observations, we suggest a new procedure which can be used in adaptive control schemes. It has been developed in the general framework of "counting of leave-out sign-dominant correlation regions" (LSCR), which is mostly being promoted by M. Campi et al. for identification problems. The procedure returns confidence regions which are guaranteed to contain true parameters with a user-chosen probability. The theoretical results are illustrated by an example of a nonminimum-phase second-order plant.

Original languageEnglish
Title of host publication2012 AMERICAN CONTROL CONFERENCE (ACC)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Print)978-1-4577-1095-7
StatePublished - 2012
EventAmerican Control Conference (ACC) - Montreal, Canada
Duration: 27 Jun 201229 Jun 2012

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


ConferenceAmerican Control Conference (ACC)

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