Robust Integral of Sign of Error and Neural Network Control for Servo System with Continuous Friction

Shubo Wang; Xuemei Ren; Jing Na; Dongwu Li

doi:10.1109/ChiCC.2016.7553902

Robust Integral of Sign of Error and Neural Network Control for Servo System with Continuous Friction

Shubo Wang
, Xuemei Ren
, Jing Na
, Dongwu Li

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

9 Citations (Scopus)

648 Downloads (Pure)

Abstract

In this paper, a novel robust controller is proposed for servo mechanisms with nonlinear friction and external disturbance. First, a continuously differentiable friction model is used to represent the nonlinear friction, and neural network (NN) is employed to approximate the nonlinear friction and external disturabance. Then, a novel robust controller is designed by using robust integral of the sign of the error (RISE) term. In order to reduce the measure noise, a desired compensation method is utilized in controller design, in which the model compensation term depends on the reference signal only. The stability of closed-loop is proved based on Lyapunov stability theory, and all signal are proved to be bounded simultaneously. Finally, comparative simulations based on a turnable servo system are implemented to validate the efficacy of the proposed method.

Original language	English
Title of host publication	Chinese Control Conference, CCC
Publisher	IEEE Computer Society
Pages	3531-3536
Number of pages	6
Volume	2016-August
ISBN (Print)	9789881563910
DOIs	https://doi.org/10.1109/ChiCC.2016.7553902
Publication status	Published - 26 Aug 2016
Event	35th Chinese Control Conference, CCC 2016 - Chengdu, China Duration: 27 Jul 2016 → 29 Jul 2016

Publication series

Name	Proceedings of the Chinese Control Conference
ISSN (Electronic)	1934-1768

Conference

Conference	35th Chinese Control Conference, CCC 2016
Country/Territory	China
City	Chengdu
Period	27/07/16 → 29/07/16

Keywords

desired compensation
friction compensation
robust integral of the sign of the error (RISE) term
Servo mechanisms

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10.1109/ChiCC.2016.7553902

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@inproceedings{24011d1a53314f0897b1f80056d3c8fb,

title = "Robust Integral of Sign of Error and Neural Network Control for Servo System with Continuous Friction",

abstract = "In this paper, a novel robust controller is proposed for servo mechanisms with nonlinear friction and external disturbance. First, a continuously differentiable friction model is used to represent the nonlinear friction, and neural network (NN) is employed to approximate the nonlinear friction and external disturabance. Then, a novel robust controller is designed by using robust integral of the sign of the error (RISE) term. In order to reduce the measure noise, a desired compensation method is utilized in controller design, in which the model compensation term depends on the reference signal only. The stability of closed-loop is proved based on Lyapunov stability theory, and all signal are proved to be bounded simultaneously. Finally, comparative simulations based on a turnable servo system are implemented to validate the efficacy of the proposed method.",

keywords = "desired compensation, friction compensation, robust integral of the sign of the error (RISE) term, Servo mechanisms",

author = "Shubo Wang and Xuemei Ren and Jing Na and Dongwu Li",

year = "2016",

month = aug,

day = "26",

doi = "10.1109/ChiCC.2016.7553902",

language = "English",

isbn = "9789881563910",

volume = "2016-August",

series = "Proceedings of the Chinese Control Conference",

publisher = "IEEE Computer Society",

pages = "3531--3536",

booktitle = "Chinese Control Conference, CCC",

address = "United States",

note = "35th Chinese Control Conference, CCC 2016 ; Conference date: 27-07-2016 Through 29-07-2016",

}

Wang, S, Ren, X, Na, J & Li, D 2016, Robust Integral of Sign of Error and Neural Network Control for Servo System with Continuous Friction. in Chinese Control Conference, CCC. vol. 2016-August, 7553902, Proceedings of the Chinese Control Conference, IEEE Computer Society, pp. 3531-3536, 35th Chinese Control Conference, CCC 2016, Chengdu, China, 27/07/16. https://doi.org/10.1109/ChiCC.2016.7553902

Robust Integral of Sign of Error and Neural Network Control for Servo System with Continuous Friction. / Wang, Shubo; Ren, Xuemei; Na, Jing et al.
Chinese Control Conference, CCC. Vol. 2016-August IEEE Computer Society, 2016. p. 3531-3536 7553902 (Proceedings of the Chinese Control Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Robust Integral of Sign of Error and Neural Network Control for Servo System with Continuous Friction

AU - Wang, Shubo

AU - Ren, Xuemei

AU - Na, Jing

AU - Li, Dongwu

PY - 2016/8/26

Y1 - 2016/8/26

N2 - In this paper, a novel robust controller is proposed for servo mechanisms with nonlinear friction and external disturbance. First, a continuously differentiable friction model is used to represent the nonlinear friction, and neural network (NN) is employed to approximate the nonlinear friction and external disturabance. Then, a novel robust controller is designed by using robust integral of the sign of the error (RISE) term. In order to reduce the measure noise, a desired compensation method is utilized in controller design, in which the model compensation term depends on the reference signal only. The stability of closed-loop is proved based on Lyapunov stability theory, and all signal are proved to be bounded simultaneously. Finally, comparative simulations based on a turnable servo system are implemented to validate the efficacy of the proposed method.

AB - In this paper, a novel robust controller is proposed for servo mechanisms with nonlinear friction and external disturbance. First, a continuously differentiable friction model is used to represent the nonlinear friction, and neural network (NN) is employed to approximate the nonlinear friction and external disturabance. Then, a novel robust controller is designed by using robust integral of the sign of the error (RISE) term. In order to reduce the measure noise, a desired compensation method is utilized in controller design, in which the model compensation term depends on the reference signal only. The stability of closed-loop is proved based on Lyapunov stability theory, and all signal are proved to be bounded simultaneously. Finally, comparative simulations based on a turnable servo system are implemented to validate the efficacy of the proposed method.

KW - desired compensation

KW - friction compensation

KW - robust integral of the sign of the error (RISE) term

KW - Servo mechanisms

UR - https://www.scopus.com/pages/publications/84987903955

U2 - 10.1109/ChiCC.2016.7553902

DO - 10.1109/ChiCC.2016.7553902

M3 - Conference Contribution (Conference Proceeding)

AN - SCOPUS:84987903955

SN - 9789881563910

VL - 2016-August

T3 - Proceedings of the Chinese Control Conference

SP - 3531

EP - 3536

BT - Chinese Control Conference, CCC

PB - IEEE Computer Society

T2 - 35th Chinese Control Conference, CCC 2016

Y2 - 27 July 2016 through 29 July 2016

ER -

Robust Integral of Sign of Error and Neural Network Control for Servo System with Continuous Friction

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