Adaptive repetitive control using a modified Filtered-X LMS algorithm

Behrooz Shahsavari; Ehsan Keikha; Fu Zhang; Roberto Horowitz

Adaptive repetitive control using a modified Filtered-X LMS algorithm

Behrooz Shahsavari, Ehsan Keikha, Fu Zhang, Roberto Horowitz

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

Abstract

In this paper we employ a modified filtered-x least mean squares (MFX-LMS) method to synthesis an adaptive repetitive controller for rejecting periodic disturbances at selective frequencies. We show how a MFX-LMS algorithm can be utilized when the reference signal is deterministic and periodic. A new adaptive step size is proposed with the motivation to improve the convergence rate of the MFX-LMS algorithm and fade the steady state excess error caused by the variation of estimated parameters in a stochastic environment. A novel secondary path modeling scheme is proposed to compensate for the modeling mismatches online. We further discuss the application of this adaptive controller in hard disk drives that use Bit Patterned Media Recording. Finally we present the results of comprehensive realistic numerical simulations and experimental implementations of the algorithms on a hard disk drive servo mechanism that is subjected to periodic disturbances known as repeatable runout.

Original language	English
Title of host publication	Active Control of Aerospace Structure; Motion Control; Aerospace Control; Assistive Robotic Systems; Bio-Inspired Systems; Biomedical/Bioengineering Applications; Building Energy Systems; Condition Based Monitoring; Control Design for Drilling Automation; Control of Ground Vehicles, Manipulators, Mechatronic Systems; Controls for Manufacturing; Distributed Control; Dynamic Modeling for Vehicle Systems; Dynamics and Control of Mobile and Locomotion Robots; Electrochemical Energy Systems
Publisher	American Society of Mechanical Engineers
ISBN (Electronic)	9780791846186
Publication status	Published - 2014
Externally published	Yes
Event	ASME 2014 Dynamic Systems and Control Conference, DSCC 2014 - San Antonio, United States Duration: 22 Oct 2014 → 24 Oct 2014

Publication series

Name	ASME 2014 Dynamic Systems and Control Conference, DSCC 2014
Volume	1

Conference

Conference	ASME 2014 Dynamic Systems and Control Conference, DSCC 2014
Country/Territory	United States
City	San Antonio
Period	22/10/14 → 24/10/14

Bibliographical note

Publisher Copyright:
Copyright © 2014 by ASME.

Access to Document

https://hdl.handle.net/1783.1/86389

Cite this

Shahsavari, B., Keikha, E., Zhang, F., & Horowitz, R. (2014). Adaptive repetitive control using a modified Filtered-X LMS algorithm. In Active Control of Aerospace Structure; Motion Control; Aerospace Control; Assistive Robotic Systems; Bio-Inspired Systems; Biomedical/Bioengineering Applications; Building Energy Systems; Condition Based Monitoring; Control Design for Drilling Automation; Control of Ground Vehicles, Manipulators, Mechatronic Systems; Controls for Manufacturing; Distributed Control; Dynamic Modeling for Vehicle Systems; Dynamics and Control of Mobile and Locomotion Robots; Electrochemical Energy Systems (ASME 2014 Dynamic Systems and Control Conference, DSCC 2014; Vol. 1). American Society of Mechanical Engineers. https://hdl.handle.net/1783.1/86389

Shahsavari, Behrooz ; Keikha, Ehsan ; Zhang, Fu et al. / Adaptive repetitive control using a modified Filtered-X LMS algorithm. Active Control of Aerospace Structure; Motion Control; Aerospace Control; Assistive Robotic Systems; Bio-Inspired Systems; Biomedical/Bioengineering Applications; Building Energy Systems; Condition Based Monitoring; Control Design for Drilling Automation; Control of Ground Vehicles, Manipulators, Mechatronic Systems; Controls for Manufacturing; Distributed Control; Dynamic Modeling for Vehicle Systems; Dynamics and Control of Mobile and Locomotion Robots; Electrochemical Energy Systems. American Society of Mechanical Engineers, 2014. (ASME 2014 Dynamic Systems and Control Conference, DSCC 2014).

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title = "Adaptive repetitive control using a modified Filtered-X LMS algorithm",

abstract = "In this paper we employ a modified filtered-x least mean squares (MFX-LMS) method to synthesis an adaptive repetitive controller for rejecting periodic disturbances at selective frequencies. We show how a MFX-LMS algorithm can be utilized when the reference signal is deterministic and periodic. A new adaptive step size is proposed with the motivation to improve the convergence rate of the MFX-LMS algorithm and fade the steady state excess error caused by the variation of estimated parameters in a stochastic environment. A novel secondary path modeling scheme is proposed to compensate for the modeling mismatches online. We further discuss the application of this adaptive controller in hard disk drives that use Bit Patterned Media Recording. Finally we present the results of comprehensive realistic numerical simulations and experimental implementations of the algorithms on a hard disk drive servo mechanism that is subjected to periodic disturbances known as repeatable runout.",

author = "Behrooz Shahsavari and Ehsan Keikha and Fu Zhang and Roberto Horowitz",

note = "Publisher Copyright: Copyright {\textcopyright} 2014 by ASME.; ASME 2014 Dynamic Systems and Control Conference, DSCC 2014 ; Conference date: 22-10-2014 Through 24-10-2014",

year = "2014",

language = "English",

series = "ASME 2014 Dynamic Systems and Control Conference, DSCC 2014",

publisher = "American Society of Mechanical Engineers",

booktitle = "Active Control of Aerospace Structure; Motion Control; Aerospace Control; Assistive Robotic Systems; Bio-Inspired Systems; Biomedical/Bioengineering Applications; Building Energy Systems; Condition Based Monitoring; Control Design for Drilling Automation; Control of Ground Vehicles, Manipulators, Mechatronic Systems; Controls for Manufacturing; Distributed Control; Dynamic Modeling for Vehicle Systems; Dynamics and Control of Mobile and Locomotion Robots; Electrochemical Energy Systems",

}

Shahsavari, B, Keikha, E, Zhang, F & Horowitz, R 2014, Adaptive repetitive control using a modified Filtered-X LMS algorithm. in Active Control of Aerospace Structure; Motion Control; Aerospace Control; Assistive Robotic Systems; Bio-Inspired Systems; Biomedical/Bioengineering Applications; Building Energy Systems; Condition Based Monitoring; Control Design for Drilling Automation; Control of Ground Vehicles, Manipulators, Mechatronic Systems; Controls for Manufacturing; Distributed Control; Dynamic Modeling for Vehicle Systems; Dynamics and Control of Mobile and Locomotion Robots; Electrochemical Energy Systems. ASME 2014 Dynamic Systems and Control Conference, DSCC 2014, vol. 1, American Society of Mechanical Engineers, ASME 2014 Dynamic Systems and Control Conference, DSCC 2014, San Antonio, United States, 22/10/14. <https://hdl.handle.net/1783.1/86389>

Adaptive repetitive control using a modified Filtered-X LMS algorithm. / Shahsavari, Behrooz; Keikha, Ehsan; Zhang, Fu et al.
Active Control of Aerospace Structure; Motion Control; Aerospace Control; Assistive Robotic Systems; Bio-Inspired Systems; Biomedical/Bioengineering Applications; Building Energy Systems; Condition Based Monitoring; Control Design for Drilling Automation; Control of Ground Vehicles, Manipulators, Mechatronic Systems; Controls for Manufacturing; Distributed Control; Dynamic Modeling for Vehicle Systems; Dynamics and Control of Mobile and Locomotion Robots; Electrochemical Energy Systems. American Society of Mechanical Engineers, 2014. (ASME 2014 Dynamic Systems and Control Conference, DSCC 2014; Vol. 1).

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

TY - GEN

T1 - Adaptive repetitive control using a modified Filtered-X LMS algorithm

AU - Shahsavari, Behrooz

AU - Keikha, Ehsan

AU - Zhang, Fu

AU - Horowitz, Roberto

PY - 2014

Y1 - 2014

N2 - In this paper we employ a modified filtered-x least mean squares (MFX-LMS) method to synthesis an adaptive repetitive controller for rejecting periodic disturbances at selective frequencies. We show how a MFX-LMS algorithm can be utilized when the reference signal is deterministic and periodic. A new adaptive step size is proposed with the motivation to improve the convergence rate of the MFX-LMS algorithm and fade the steady state excess error caused by the variation of estimated parameters in a stochastic environment. A novel secondary path modeling scheme is proposed to compensate for the modeling mismatches online. We further discuss the application of this adaptive controller in hard disk drives that use Bit Patterned Media Recording. Finally we present the results of comprehensive realistic numerical simulations and experimental implementations of the algorithms on a hard disk drive servo mechanism that is subjected to periodic disturbances known as repeatable runout.

AB - In this paper we employ a modified filtered-x least mean squares (MFX-LMS) method to synthesis an adaptive repetitive controller for rejecting periodic disturbances at selective frequencies. We show how a MFX-LMS algorithm can be utilized when the reference signal is deterministic and periodic. A new adaptive step size is proposed with the motivation to improve the convergence rate of the MFX-LMS algorithm and fade the steady state excess error caused by the variation of estimated parameters in a stochastic environment. A novel secondary path modeling scheme is proposed to compensate for the modeling mismatches online. We further discuss the application of this adaptive controller in hard disk drives that use Bit Patterned Media Recording. Finally we present the results of comprehensive realistic numerical simulations and experimental implementations of the algorithms on a hard disk drive servo mechanism that is subjected to periodic disturbances known as repeatable runout.

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M3 - Conference Paper published in a book

AN - SCOPUS:84929378057

T3 - ASME 2014 Dynamic Systems and Control Conference, DSCC 2014

BT - Active Control of Aerospace Structure; Motion Control; Aerospace Control; Assistive Robotic Systems; Bio-Inspired Systems; Biomedical/Bioengineering Applications; Building Energy Systems; Condition Based Monitoring; Control Design for Drilling Automation; Control of Ground Vehicles, Manipulators, Mechatronic Systems; Controls for Manufacturing; Distributed Control; Dynamic Modeling for Vehicle Systems; Dynamics and Control of Mobile and Locomotion Robots; Electrochemical Energy Systems

PB - American Society of Mechanical Engineers

T2 - ASME 2014 Dynamic Systems and Control Conference, DSCC 2014

Y2 - 22 October 2014 through 24 October 2014

ER -

Shahsavari B, Keikha E, Zhang F, Horowitz R. Adaptive repetitive control using a modified Filtered-X LMS algorithm. In Active Control of Aerospace Structure; Motion Control; Aerospace Control; Assistive Robotic Systems; Bio-Inspired Systems; Biomedical/Bioengineering Applications; Building Energy Systems; Condition Based Monitoring; Control Design for Drilling Automation; Control of Ground Vehicles, Manipulators, Mechatronic Systems; Controls for Manufacturing; Distributed Control; Dynamic Modeling for Vehicle Systems; Dynamics and Control of Mobile and Locomotion Robots; Electrochemical Energy Systems. American Society of Mechanical Engineers. 2014. (ASME 2014 Dynamic Systems and Control Conference, DSCC 2014).

Adaptive repetitive control using a modified Filtered-X LMS algorithm

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