Neural network feedforward control for mechanical systems with external disturbances

Xuemei Ren; Frank L. Lewis; Shuzhi Sam Ge; Jingliang Zhang

doi:10.1109/CDC.2007.4434457

Neural network feedforward control for mechanical systems with external disturbances

Xuemei Ren^*
, Frank L. Lewis
, Shuzhi Sam Ge
, Jingliang Zhang

^*Corresponding author for this work

School of Automation

IEEE
University of Texas at Arlington
National University of Singapore
Agency for Science, Technology and Research, Singapore

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

1 Citation (Scopus)

Abstract

In this paper, a novel feedforward control based on accelerometer measurements is proposed for mechanical systems with external disturbances. The control scheme includes a feedback controller and a neural network feedforward compensator. The feedback controller is employed to guarantee the stability of the mechanical systems, while the neural network is used to provide the required feedforward compensation input for trajectory tracking with the help of a sensor to detect external vibrations. Dynamics knowledge of the plant, disturbances and the sensor is not required. The stability of the proposed scheme is analyzed by the Lyapunov criterion. Simulation results show that the proposed controller performs well for a hard disk drive system and a two-link manipulator.

Original language	English
Title of host publication	Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4687-4692
Number of pages	6
ISBN (Print)	1424414989, 9781424414987
DOIs	https://doi.org/10.1109/CDC.2007.4434457
Publication status	Published - 2007
Event	46th IEEE Conference on Decision and Control 2007, CDC - New Orleans, LA, United States Duration: 12 Dec 2007 → 14 Dec 2007

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	46th IEEE Conference on Decision and Control 2007, CDC
Country/Territory	United States
City	New Orleans, LA
Period	12/12/07 → 14/12/07

Access to Document

10.1109/CDC.2007.4434457

Cite this

Ren, X., Lewis, F. L., Ge, S. S., & Zhang, J. (2007). Neural network feedforward control for mechanical systems with external disturbances. In Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC (pp. 4687-4692). Article 4434457 (Proceedings of the IEEE Conference on Decision and Control). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2007.4434457

@inproceedings{0296288b63644203b439998f2246650d,

title = "Neural network feedforward control for mechanical systems with external disturbances",

abstract = "In this paper, a novel feedforward control based on accelerometer measurements is proposed for mechanical systems with external disturbances. The control scheme includes a feedback controller and a neural network feedforward compensator. The feedback controller is employed to guarantee the stability of the mechanical systems, while the neural network is used to provide the required feedforward compensation input for trajectory tracking with the help of a sensor to detect external vibrations. Dynamics knowledge of the plant, disturbances and the sensor is not required. The stability of the proposed scheme is analyzed by the Lyapunov criterion. Simulation results show that the proposed controller performs well for a hard disk drive system and a two-link manipulator.",

author = "Xuemei Ren and Lewis, \{Frank L.\} and Ge, \{Shuzhi Sam\} and Jingliang Zhang",

year = "2007",

doi = "10.1109/CDC.2007.4434457",

language = "English",

isbn = "1424414989",

series = "Proceedings of the IEEE Conference on Decision and Control",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "4687--4692",

booktitle = "Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC",

address = "United States",

note = "46th IEEE Conference on Decision and Control 2007, CDC ; Conference date: 12-12-2007 Through 14-12-2007",

}

Ren, X, Lewis, FL, Ge, SS & Zhang, J 2007, Neural network feedforward control for mechanical systems with external disturbances. in Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC., 4434457, Proceedings of the IEEE Conference on Decision and Control, Institute of Electrical and Electronics Engineers Inc., pp. 4687-4692, 46th IEEE Conference on Decision and Control 2007, CDC, New Orleans, LA, United States, 12/12/07. https://doi.org/10.1109/CDC.2007.4434457

Neural network feedforward control for mechanical systems with external disturbances. / Ren, Xuemei; Lewis, Frank L.; Ge, Shuzhi Sam et al.
Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC. Institute of Electrical and Electronics Engineers Inc., 2007. p. 4687-4692 4434457 (Proceedings of the IEEE Conference on Decision and Control).

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

TY - GEN

T1 - Neural network feedforward control for mechanical systems with external disturbances

AU - Ren, Xuemei

AU - Lewis, Frank L.

AU - Ge, Shuzhi Sam

AU - Zhang, Jingliang

PY - 2007

Y1 - 2007

N2 - In this paper, a novel feedforward control based on accelerometer measurements is proposed for mechanical systems with external disturbances. The control scheme includes a feedback controller and a neural network feedforward compensator. The feedback controller is employed to guarantee the stability of the mechanical systems, while the neural network is used to provide the required feedforward compensation input for trajectory tracking with the help of a sensor to detect external vibrations. Dynamics knowledge of the plant, disturbances and the sensor is not required. The stability of the proposed scheme is analyzed by the Lyapunov criterion. Simulation results show that the proposed controller performs well for a hard disk drive system and a two-link manipulator.

AB - In this paper, a novel feedforward control based on accelerometer measurements is proposed for mechanical systems with external disturbances. The control scheme includes a feedback controller and a neural network feedforward compensator. The feedback controller is employed to guarantee the stability of the mechanical systems, while the neural network is used to provide the required feedforward compensation input for trajectory tracking with the help of a sensor to detect external vibrations. Dynamics knowledge of the plant, disturbances and the sensor is not required. The stability of the proposed scheme is analyzed by the Lyapunov criterion. Simulation results show that the proposed controller performs well for a hard disk drive system and a two-link manipulator.

UR - https://www.scopus.com/pages/publications/62749188758

U2 - 10.1109/CDC.2007.4434457

DO - 10.1109/CDC.2007.4434457

M3 - Conference contribution

AN - SCOPUS:62749188758

SN - 1424414989

SN - 9781424414987

T3 - Proceedings of the IEEE Conference on Decision and Control

SP - 4687

EP - 4692

BT - Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 46th IEEE Conference on Decision and Control 2007, CDC

Y2 - 12 December 2007 through 14 December 2007

ER -

Ren X, Lewis FL, Ge SS, Zhang J. Neural network feedforward control for mechanical systems with external disturbances. In Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC. Institute of Electrical and Electronics Engineers Inc. 2007. p. 4687-4692. 4434457. (Proceedings of the IEEE Conference on Decision and Control). doi: 10.1109/CDC.2007.4434457

Neural network feedforward control for mechanical systems with external disturbances

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this