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Avtomatika i Telemekhanika, 2018, Issue 1, Pages 33–51 (Mi at14708)  
Topical issue

Design of Pareto-optimal linear quadratic estimates, filters and controllers

D. V. Balandina, M. M. Koganb

a Lobachevsky Nizhny Novgorod State University, Nizhny Novgorod, Russia
b Nizhny Novgorod State University of Architecture and Civil Engineering, Nizhny Novgorod, Russia
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Abstract: Consideration was given to the multicriterial approach to the problems of estimation, filtration, and control; among them under uncertainty in regard to the covariance of random factors. The Pareto-optimal estimates, filters, and controllers in the problems where the data can arrive from any of the more than one data sources with various statistical characteristics, as well as in the dual problems where it is required to minimize the rms deviations of more than one objective output, were designed on the basis of the Germeier convolution and the apparatus of linear matrix inequalities.
Keywords: estimation, filtration, control, multicriterial optimization, Pareto set, Germeier convolution.
Funding agency Grant number
Russian Foundation for Basic Research 16-01-00606
This work was supported by the Russian Foundation for Basic Research, project no. 16-01-00606.
Presented by the member of Editorial Board: A. I. Kibzun

Received: 20.03.2017
English version:
Automation and Remote Control, 2018, Volume 79, Issue 1, Pages 24–38
DOI: https://doi.org/10.1134/S0005117918010034
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: D. V. Balandin, M. M. Kogan, “Design of Pareto-optimal linear quadratic estimates, filters and controllers”, Avtomat. i Telemekh., 2018, no. 1, 33–51; Autom. Remote Control, 79:1 (2018), 24–38
Citation in format AMSBIB
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