Reconstructed multi-innovation gradient algorithm for the identification of sandwich systems

Linwei Li; Xuemei Ren; Yongfeng Lv

doi:10.1007/978-981-13-2288-4_30

Reconstructed multi-innovation gradient algorithm for the identification of sandwich systems

Linwei Li
, Xuemei Ren^*
, Yongfeng Lv

^*Corresponding author for this work

School of Automation

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Inspired by multi-innovation stochastic gradient identification algorithm, a reconstructed multi-innovation stochastic gradient identification algorithm (RMISG) is presented to estimate the parameters of sandwich systems in this paper. Compared with the traditional multi-innovation stochastic gradient identification algorithm, the RMISG is constructed by using the multistep update principle which solves the multi-innovation length problem and improves the performance of the identification algorithm. To decrease the calculation burden of the RMISG, the key-term separation principle is introduced to deal with the identification model of sandwich systems. Finally, simulation example is given to validate the availability of the proposed estimator.

Original language	English
Title of host publication	Proceedings of 2018 Chinese Intelligent Systems Conference - Volume I
Editors	Yingmin Jia, Junping Du, Weicun Zhang
Publisher	Springer Verlag
Pages	301-309
Number of pages	9
ISBN (Print)	9789811322877
DOIs	https://doi.org/10.1007/978-981-13-2288-4_30
Publication status	Published - 2019
Event	Chinese Intelligent Systems Conference, CISC 2018 - Wenzhou, China Duration: 1 Jan 2019 → 1 Jan 2019

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	528
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	Chinese Intelligent Systems Conference, CISC 2018
Country/Territory	China
City	Wenzhou
Period	1/01/19 → 1/01/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

Key-term separation principle
Multi-innovation gradient algorithm
Parameter estimation
Sandwich systems

Access to Document

10.1007/978-981-13-2288-4_30

Cite this

@inproceedings{0824f2401f444a6d9e7e375bf9367b10,

title = "Reconstructed multi-innovation gradient algorithm for the identification of sandwich systems",

abstract = "Inspired by multi-innovation stochastic gradient identification algorithm, a reconstructed multi-innovation stochastic gradient identification algorithm (RMISG) is presented to estimate the parameters of sandwich systems in this paper. Compared with the traditional multi-innovation stochastic gradient identification algorithm, the RMISG is constructed by using the multistep update principle which solves the multi-innovation length problem and improves the performance of the identification algorithm. To decrease the calculation burden of the RMISG, the key-term separation principle is introduced to deal with the identification model of sandwich systems. Finally, simulation example is given to validate the availability of the proposed estimator.",

keywords = "Key-term separation principle, Multi-innovation gradient algorithm, Parameter estimation, Sandwich systems",

author = "Linwei Li and Xuemei Ren and Yongfeng Lv",

note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2019.; Chinese Intelligent Systems Conference, CISC 2018 ; Conference date: 01-01-2019 Through 01-01-2019",

year = "2019",

doi = "10.1007/978-981-13-2288-4\_30",

language = "English",

isbn = "9789811322877",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Verlag",

pages = "301--309",

editor = "Yingmin Jia and Junping Du and Weicun Zhang",

booktitle = "Proceedings of 2018 Chinese Intelligent Systems Conference - Volume I",

address = "Germany",

}

Li, L, Ren, X & Lv, Y 2019, Reconstructed multi-innovation gradient algorithm for the identification of sandwich systems. in Y Jia, J Du & W Zhang (eds), Proceedings of 2018 Chinese Intelligent Systems Conference - Volume I. Lecture Notes in Electrical Engineering, vol. 528, Springer Verlag, pp. 301-309, Chinese Intelligent Systems Conference, CISC 2018, Wenzhou, China, 1/01/19. https://doi.org/10.1007/978-981-13-2288-4_30

Reconstructed multi-innovation gradient algorithm for the identification of sandwich systems. / Li, Linwei; Ren, Xuemei; Lv, Yongfeng.
Proceedings of 2018 Chinese Intelligent Systems Conference - Volume I. ed. / Yingmin Jia; Junping Du; Weicun Zhang. Springer Verlag, 2019. p. 301-309 (Lecture Notes in Electrical Engineering; Vol. 528).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Reconstructed multi-innovation gradient algorithm for the identification of sandwich systems

AU - Li, Linwei

AU - Ren, Xuemei

AU - Lv, Yongfeng

N1 - Publisher Copyright: © Springer Nature Singapore Pte Ltd. 2019.

PY - 2019

Y1 - 2019

N2 - Inspired by multi-innovation stochastic gradient identification algorithm, a reconstructed multi-innovation stochastic gradient identification algorithm (RMISG) is presented to estimate the parameters of sandwich systems in this paper. Compared with the traditional multi-innovation stochastic gradient identification algorithm, the RMISG is constructed by using the multistep update principle which solves the multi-innovation length problem and improves the performance of the identification algorithm. To decrease the calculation burden of the RMISG, the key-term separation principle is introduced to deal with the identification model of sandwich systems. Finally, simulation example is given to validate the availability of the proposed estimator.

AB - Inspired by multi-innovation stochastic gradient identification algorithm, a reconstructed multi-innovation stochastic gradient identification algorithm (RMISG) is presented to estimate the parameters of sandwich systems in this paper. Compared with the traditional multi-innovation stochastic gradient identification algorithm, the RMISG is constructed by using the multistep update principle which solves the multi-innovation length problem and improves the performance of the identification algorithm. To decrease the calculation burden of the RMISG, the key-term separation principle is introduced to deal with the identification model of sandwich systems. Finally, simulation example is given to validate the availability of the proposed estimator.

KW - Key-term separation principle

KW - Multi-innovation gradient algorithm

KW - Parameter estimation

KW - Sandwich systems

UR - https://www.scopus.com/pages/publications/85055135149

U2 - 10.1007/978-981-13-2288-4_30

DO - 10.1007/978-981-13-2288-4_30

M3 - Conference contribution

AN - SCOPUS:85055135149

SN - 9789811322877

T3 - Lecture Notes in Electrical Engineering

SP - 301

EP - 309

BT - Proceedings of 2018 Chinese Intelligent Systems Conference - Volume I

A2 - Jia, Yingmin

A2 - Du, Junping

A2 - Zhang, Weicun

PB - Springer Verlag

T2 - Chinese Intelligent Systems Conference, CISC 2018

Y2 - 1 January 2019 through 1 January 2019

ER -

Reconstructed multi-innovation gradient algorithm for the identification of sandwich systems

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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