Norm optimal iterative learning identification for linear time-varying systems

Nanjun Liu; Andrew G Alleyne

doi:10.1115/DSCC2012-MOVIC2012-8589

Norm optimal iterative learning identification for linear time-varying systems

Nanjun Liu, Andrew G Alleyne

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

Abstract

This article presents a new identification method for discrete-time, single-input single-output, linear time-varying (LTV) plant utilizing the input and output data. This method applies specifically to plants that are able to repeat their trajectories. The identification learning law is determined through an optimization framework, which is similar in nature to the norm optimal design for Iterative Learning Control (ILC). Conditions for stability and convergence are obtained in the study. The design is verified using a numerical example.

Original language	English (US)
Title of host publication	ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012
Pages	889-896
Number of pages	8
DOIs	https://doi.org/10.1115/DSCC2012-MOVIC2012-8589
State	Published - 2012
Event	ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012 - Fort Lauderdale, FL, United States Duration: Oct 17 2012 → Oct 19 2012

Publication series

Name	ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012
Volume	1

Other

Other	ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012
Country/Territory	United States
City	Fort Lauderdale, FL
Period	10/17/12 → 10/19/12

ASJC Scopus subject areas

Control and Systems Engineering

Online availability

10.1115/DSCC2012-MOVIC2012-8589

Library availability

Discover UIUC Full Text

Cite this

Liu, N., & Alleyne, A. G. (2012). Norm optimal iterative learning identification for linear time-varying systems. In ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012 (pp. 889-896). (ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012; Vol. 1). https://doi.org/10.1115/DSCC2012-MOVIC2012-8589

Norm optimal iterative learning identification for linear time-varying systems. / Liu, Nanjun; Alleyne, Andrew G.
ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012. 2012. p. 889-896 (ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012; Vol. 1).

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

Liu, N & Alleyne, AG 2012, Norm optimal iterative learning identification for linear time-varying systems. in ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012. ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012, vol. 1, pp. 889-896, ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012, Fort Lauderdale, FL, United States, 10/17/12. https://doi.org/10.1115/DSCC2012-MOVIC2012-8589

Liu N, Alleyne AG. Norm optimal iterative learning identification for linear time-varying systems. In ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012. 2012. p. 889-896. (ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012). doi: 10.1115/DSCC2012-MOVIC2012-8589

Liu, Nanjun ; Alleyne, Andrew G. / Norm optimal iterative learning identification for linear time-varying systems. ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012. 2012. pp. 889-896 (ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012).

@inproceedings{fe41d7b5b89f47b09033ee0d0fbdf683,

title = "Norm optimal iterative learning identification for linear time-varying systems",

abstract = "This article presents a new identification method for discrete-time, single-input single-output, linear time-varying (LTV) plant utilizing the input and output data. This method applies specifically to plants that are able to repeat their trajectories. The identification learning law is determined through an optimization framework, which is similar in nature to the norm optimal design for Iterative Learning Control (ILC). Conditions for stability and convergence are obtained in the study. The design is verified using a numerical example.",

author = "Nanjun Liu and Alleyne, {Andrew G}",

year = "2012",

doi = "10.1115/DSCC2012-MOVIC2012-8589",

language = "English (US)",

isbn = "9780791845295",

series = "ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012",

pages = "889--896",

booktitle = "ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012",

note = "ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012 ; Conference date: 17-10-2012 Through 19-10-2012",

}

TY - GEN

T1 - Norm optimal iterative learning identification for linear time-varying systems

AU - Liu, Nanjun

AU - Alleyne, Andrew G

PY - 2012

Y1 - 2012

N2 - This article presents a new identification method for discrete-time, single-input single-output, linear time-varying (LTV) plant utilizing the input and output data. This method applies specifically to plants that are able to repeat their trajectories. The identification learning law is determined through an optimization framework, which is similar in nature to the norm optimal design for Iterative Learning Control (ILC). Conditions for stability and convergence are obtained in the study. The design is verified using a numerical example.

AB - This article presents a new identification method for discrete-time, single-input single-output, linear time-varying (LTV) plant utilizing the input and output data. This method applies specifically to plants that are able to repeat their trajectories. The identification learning law is determined through an optimization framework, which is similar in nature to the norm optimal design for Iterative Learning Control (ILC). Conditions for stability and convergence are obtained in the study. The design is verified using a numerical example.

UR - http://www.scopus.com/inward/record.url?scp=84885913493&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84885913493&partnerID=8YFLogxK

U2 - 10.1115/DSCC2012-MOVIC2012-8589

DO - 10.1115/DSCC2012-MOVIC2012-8589

M3 - Conference contribution

AN - SCOPUS:84885913493

SN - 9780791845295

T3 - ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012

SP - 889

EP - 896

BT - ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012

T2 - ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012

Y2 - 17 October 2012 through 19 October 2012

ER -

Norm optimal iterative learning identification for linear time-varying systems

Abstract

Publication series

Other

ASJC Scopus subject areas

Online availability

Library availability

Related links

Fingerprint

Cite this