Identification of Decentralized System with Common Parameters

Mizuho Takeuchi, Takahiro Kawaguchi, Masaki Inoue, Masaru Naruoka, Shuichi Adachi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper addresses a system identification problem for multiple isolated systems whose parameters are partially identical. An approach to the problem is a centralized identification; a single estimator collects all the input-output data from all of the systems to estimate their parameters at once. However, the approach can be practically infeasible when it is applied to a large number of systems due to the limitation of computational and communication resources. To solve the issue, we propose a method of a networked identification composed of two stages: 1) Multiple estimators collect the data from their own target systems to independently derive temporary estimates of their parameters and a covariance matrix of the estimates. 2) Then, with communicating the temporary estimates and the covariance matrix, they update their estimates. We also show the optimality of the proposed networked identification method with respect to the modeling accuracy, which is equivalently achieved by the centralized identification. Finally, we show the effectiveness of the proposed method in a numerical simulation.

Original languageEnglish
Title of host publication2018 IEEE Conference on Control Technology and Applications, CCTA 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1508-1513
Number of pages6
ISBN (Electronic)9781538676981
DOIs
Publication statusPublished - 2018 Oct 26
Event2nd IEEE Conference on Control Technology and Applications, CCTA 2018 - Copenhagen, Denmark
Duration: 2018 Aug 212018 Aug 24

Other

Other2nd IEEE Conference on Control Technology and Applications, CCTA 2018
CountryDenmark
CityCopenhagen
Period18/8/2118/8/24

Fingerprint

Covariance matrix
Decentralized
Estimate
Identification (control systems)
Communication
Computer simulation
Estimator
Identification Problem
System Identification
Optimality
Update
Numerical Simulation
Resources
Target
Output
Modeling

ASJC Scopus subject areas

  • Aerospace Engineering
  • Control and Optimization
  • Automotive Engineering
  • Safety, Risk, Reliability and Quality

Cite this

Takeuchi, M., Kawaguchi, T., Inoue, M., Naruoka, M., & Adachi, S. (2018). Identification of Decentralized System with Common Parameters. In 2018 IEEE Conference on Control Technology and Applications, CCTA 2018 (pp. 1508-1513). [8511472] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCTA.2018.8511472

Identification of Decentralized System with Common Parameters. / Takeuchi, Mizuho; Kawaguchi, Takahiro; Inoue, Masaki; Naruoka, Masaru; Adachi, Shuichi.

2018 IEEE Conference on Control Technology and Applications, CCTA 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1508-1513 8511472.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Takeuchi, M, Kawaguchi, T, Inoue, M, Naruoka, M & Adachi, S 2018, Identification of Decentralized System with Common Parameters. in 2018 IEEE Conference on Control Technology and Applications, CCTA 2018., 8511472, Institute of Electrical and Electronics Engineers Inc., pp. 1508-1513, 2nd IEEE Conference on Control Technology and Applications, CCTA 2018, Copenhagen, Denmark, 18/8/21. https://doi.org/10.1109/CCTA.2018.8511472
Takeuchi M, Kawaguchi T, Inoue M, Naruoka M, Adachi S. Identification of Decentralized System with Common Parameters. In 2018 IEEE Conference on Control Technology and Applications, CCTA 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1508-1513. 8511472 https://doi.org/10.1109/CCTA.2018.8511472
Takeuchi, Mizuho ; Kawaguchi, Takahiro ; Inoue, Masaki ; Naruoka, Masaru ; Adachi, Shuichi. / Identification of Decentralized System with Common Parameters. 2018 IEEE Conference on Control Technology and Applications, CCTA 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1508-1513
@inproceedings{e1d9cf5361d043cdad820e869cda4660,
title = "Identification of Decentralized System with Common Parameters",
abstract = "This paper addresses a system identification problem for multiple isolated systems whose parameters are partially identical. An approach to the problem is a centralized identification; a single estimator collects all the input-output data from all of the systems to estimate their parameters at once. However, the approach can be practically infeasible when it is applied to a large number of systems due to the limitation of computational and communication resources. To solve the issue, we propose a method of a networked identification composed of two stages: 1) Multiple estimators collect the data from their own target systems to independently derive temporary estimates of their parameters and a covariance matrix of the estimates. 2) Then, with communicating the temporary estimates and the covariance matrix, they update their estimates. We also show the optimality of the proposed networked identification method with respect to the modeling accuracy, which is equivalently achieved by the centralized identification. Finally, we show the effectiveness of the proposed method in a numerical simulation.",
author = "Mizuho Takeuchi and Takahiro Kawaguchi and Masaki Inoue and Masaru Naruoka and Shuichi Adachi",
year = "2018",
month = "10",
day = "26",
doi = "10.1109/CCTA.2018.8511472",
language = "English",
pages = "1508--1513",
booktitle = "2018 IEEE Conference on Control Technology and Applications, CCTA 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Identification of Decentralized System with Common Parameters

AU - Takeuchi, Mizuho

AU - Kawaguchi, Takahiro

AU - Inoue, Masaki

AU - Naruoka, Masaru

AU - Adachi, Shuichi

PY - 2018/10/26

Y1 - 2018/10/26

N2 - This paper addresses a system identification problem for multiple isolated systems whose parameters are partially identical. An approach to the problem is a centralized identification; a single estimator collects all the input-output data from all of the systems to estimate their parameters at once. However, the approach can be practically infeasible when it is applied to a large number of systems due to the limitation of computational and communication resources. To solve the issue, we propose a method of a networked identification composed of two stages: 1) Multiple estimators collect the data from their own target systems to independently derive temporary estimates of their parameters and a covariance matrix of the estimates. 2) Then, with communicating the temporary estimates and the covariance matrix, they update their estimates. We also show the optimality of the proposed networked identification method with respect to the modeling accuracy, which is equivalently achieved by the centralized identification. Finally, we show the effectiveness of the proposed method in a numerical simulation.

AB - This paper addresses a system identification problem for multiple isolated systems whose parameters are partially identical. An approach to the problem is a centralized identification; a single estimator collects all the input-output data from all of the systems to estimate their parameters at once. However, the approach can be practically infeasible when it is applied to a large number of systems due to the limitation of computational and communication resources. To solve the issue, we propose a method of a networked identification composed of two stages: 1) Multiple estimators collect the data from their own target systems to independently derive temporary estimates of their parameters and a covariance matrix of the estimates. 2) Then, with communicating the temporary estimates and the covariance matrix, they update their estimates. We also show the optimality of the proposed networked identification method with respect to the modeling accuracy, which is equivalently achieved by the centralized identification. Finally, we show the effectiveness of the proposed method in a numerical simulation.

UR - http://www.scopus.com/inward/record.url?scp=85056807005&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85056807005&partnerID=8YFLogxK

U2 - 10.1109/CCTA.2018.8511472

DO - 10.1109/CCTA.2018.8511472

M3 - Conference contribution

AN - SCOPUS:85056807005

SP - 1508

EP - 1513

BT - 2018 IEEE Conference on Control Technology and Applications, CCTA 2018

PB - Institute of Electrical and Electronics Engineers Inc.

ER -