Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/92250
Title: Regularization in the Problem of Minimization of Stochastic Sensitivity
Authors: Bashkirtseva, I.
Ryashko, L.
Issue Date: 2018
Publisher: Elsevier B.V.
Citation: Bashkirtseva I. Regularization in the Problem of Minimization of Stochastic Sensitivity / I. Bashkirtseva, L. Ryashko. — DOI 10.1016/j.ifacol.2018.11.490 // IFAC-PapersOnLine. — 2018. — Vol. 32. — Iss. 51. — P. 606-609.
Abstract: We consider a problem of the construction of feedback regulator which synthesizes the assigned stochastic sensitivity of the equilibrium in stochastically forced nonlinear dynamic system. In the case of complete information, it is shown that this problem can be reduced to the solution of the matrix algebraic equation. A presence of noise in measurements deforms the stochastic sensitivity. We find conditions when such deformation is extremely large, and the considered problem is ill-posed. For this ill-posed problem, a regularization method is suggested. We propose an analytical approach which allows us to take into account a presence of noise in measurements when we construct an optimal feedback regulator. General theoretical results are illustrated by examples. © 2018
Keywords: FEEDBACK REGULATORS
ILL-POSEDNESS
RANDOM DISTURBANCES
REGULARIZATION
STOCHASTIC SENSITIVITY
NONLINEAR DYNAMICAL SYSTEMS
ALGEBRAIC EQUATIONS
ANALYTICAL APPROACH
COMPLETE INFORMATION
ILL-POSEDNESS
RANDOM DISTURBANCES
REGULARIZATION
REGULARIZATION METHODS
STOCHASTIC SENSITIVITY
STOCHASTIC SYSTEMS
URI: http://elar.urfu.ru/handle/10995/92250
Access: info:eu-repo/semantics/openAccess
RSCI ID: 38676584
SCOPUS ID: 85058164397
WOS ID: 000453278300114
PURE ID: 8424254
ISSN: 2405-8963
DOI: 10.1016/j.ifacol.2018.11.490
Appears in Collections:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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