Standard

Cyclic Stochastic Approximation with Disturbance on Input in the Parameter Tracking Problem Based on a Multiagent Algorithm. / Granichin, O. N.; Erofeeva, V. A.

In: Automation and Remote Control, Vol. 79, No. 6, 01.06.2018, p. 1013-1028.

Research output: Contribution to journal › Article › peer-review

Harvard

Granichin, ON & Erofeeva, VA 2018, 'Cyclic Stochastic Approximation with Disturbance on Input in the Parameter Tracking Problem Based on a Multiagent Algorithm', Automation and Remote Control, vol. 79, no. 6, pp. 1013-1028. https://doi.org/10.1134/S0005117918060036

APA

Granichin, O. N., & Erofeeva, V. A. (2018). Cyclic Stochastic Approximation with Disturbance on Input in the Parameter Tracking Problem Based on a Multiagent Algorithm. Automation and Remote Control, 79(6), 1013-1028. https://doi.org/10.1134/S0005117918060036

Vancouver

Granichin ON, Erofeeva VA. Cyclic Stochastic Approximation with Disturbance on Input in the Parameter Tracking Problem Based on a Multiagent Algorithm. Automation and Remote Control. 2018 Jun 1;79(6):1013-1028. https://doi.org/10.1134/S0005117918060036

Author

Granichin, O. N. ; Erofeeva, V. A. / Cyclic Stochastic Approximation with Disturbance on Input in the Parameter Tracking Problem Based on a Multiagent Algorithm. In: Automation and Remote Control. 2018 ; Vol. 79, No. 6. pp. 1013-1028.

BibTeX

@article{ff373ad5a7614b7cb57061b6b21ca36b,
title = "Cyclic Stochastic Approximation with Disturbance on Input in the Parameter Tracking Problem Based on a Multiagent Algorithm",
abstract = "We consider the possibilities of using cyclic stochastic approximation for solving optimization problems of a nonstationary functional of the data produced by distributed observers (sensors) under constraints on the possibilities of simultaneous communication between the observers themselves. We achieve tracking the optimal value of parameters up to a certain level of quality with a multi-agent algorithm. The efficiency of the proposed approach is illustrated by an example of modeling the process of tracking the trajectories of a group of moving objects using a set of spatially distributed sensors.",
keywords = "stochastic approximation, object tracking, nonstationary functional, parameter tracking, cyclic approach, multi-agent algorithm, NONCONVEX OPTIMIZATION, IDENTIFICATION, CONSENSUS, SYSTEMS, NETWORK",
author = "Granichin, {O. N.} and Erofeeva, {V. A.}",
year = "2018",
month = jun,
day = "1",
doi = "10.1134/S0005117918060036",
language = "Английский",
volume = "79",
pages = "1013--1028",
journal = "Automation and Remote Control",
issn = "0005-1179",
publisher = "МАИК {"}Наука/Интерпериодика{"}",
number = "6",

}

RIS

TY - JOUR

T1 - Cyclic Stochastic Approximation with Disturbance on Input in the Parameter Tracking Problem Based on a Multiagent Algorithm

AU - Granichin, O. N.

AU - Erofeeva, V. A.

PY - 2018/6/1

Y1 - 2018/6/1

N2 - We consider the possibilities of using cyclic stochastic approximation for solving optimization problems of a nonstationary functional of the data produced by distributed observers (sensors) under constraints on the possibilities of simultaneous communication between the observers themselves. We achieve tracking the optimal value of parameters up to a certain level of quality with a multi-agent algorithm. The efficiency of the proposed approach is illustrated by an example of modeling the process of tracking the trajectories of a group of moving objects using a set of spatially distributed sensors.

AB - We consider the possibilities of using cyclic stochastic approximation for solving optimization problems of a nonstationary functional of the data produced by distributed observers (sensors) under constraints on the possibilities of simultaneous communication between the observers themselves. We achieve tracking the optimal value of parameters up to a certain level of quality with a multi-agent algorithm. The efficiency of the proposed approach is illustrated by an example of modeling the process of tracking the trajectories of a group of moving objects using a set of spatially distributed sensors.

KW - stochastic approximation

KW - object tracking

KW - nonstationary functional

KW - parameter tracking

KW - cyclic approach

KW - multi-agent algorithm

KW - NONCONVEX OPTIMIZATION

KW - IDENTIFICATION

KW - CONSENSUS

KW - SYSTEMS

KW - NETWORK

UR - http://www.scopus.com/inward/record.url?scp=85048692786&partnerID=8YFLogxK

U2 - 10.1134/S0005117918060036

DO - 10.1134/S0005117918060036

M3 - статья

VL - 79

SP - 1013

EP - 1028

JO - Automation and Remote Control

JF - Automation and Remote Control

SN - 0005-1179

IS - 6

ER -

ID: 32478577