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Avtomatika i Telemekhanika, 2020, Issue 3, Pages 132–156
DOI: https://doi.org/10.31857/S0005231020030083 (Mi at15439) 		 
This article is cited in 13 scientific papers (total in 13 papers)

Topical issue

Iterative learning control of a multiagent system under random perturbations

P. V. Pakshin, A. S. Koposov, Yu. P. Emelianova

Arzamas Polytechnic Institute of R.E. Alekseev Nizhny Novgorod State Technical University, Arzamas, Russia
Full-text PDF (3112 kB) Citations (13)
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DOI: https://doi.org/10.31857/S0005231020030083
Abstract: A multiagent system in which each of the agents is described by a linear discrete-time model with random perturbations (external random disturbances affecting the plant and measurement noises) is considered. Networked modifications of iterative learning control laws based on minimizing the deviations from a reference model and also based on the theory of stochastic stability of repetitive processes using the divergent method of vector Lyapunov functions are proposed. These modifications are compared with each other by an illustrative example of iterative learning control for a group of gantry robots.
Keywords: multiagent system, stochastic system, networked control, iterative learning control, reference model, repetitive processes, vector Lyapunov function.
Funding agency Grant number
Russian Foundation for Basic Research 19-08-00528_а
This work was supported by the Russian Foundation for Basic Research, project no. 19-08-00528_a.
Presented by the member of Editorial Board: E. Ya. Rubinovich

Received: 20.06.2019
Revised: 12.08.2019
Accepted: 26.09.2019
English version:
Automation and Remote Control, 2020, Volume 81, Issue 3, Pages 483–502
DOI: https://doi.org/10.1134/S0005117920030078
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: P. V. Pakshin, A. S. Koposov, Yu. P. Emelianova, “Iterative learning control of a multiagent system under random perturbations”, Avtomat. i Telemekh., 2020, no. 3, 132–156; Autom. Remote Control, 81:3 (2020), 483–502
Citation in format AMSBIB
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  • https://www.mathnet.ru/eng/at/y2020/i3/p132
    • This publication is cited in the following 13 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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