Adaptive neural control for uncertain nonlinear systems in pure-feedback form with hysteresis input

Beibei Ren; Shuzhi Sam Ge; Tong Heng Lee; Chun Yi Su

doi:10.1109/CDC.2008.4739240

Adaptive neural control for uncertain nonlinear systems in pure-feedback form with hysteresis input

Beibei Ren, Shuzhi Sam Ge, Tong Heng Lee, Chun Yi Su

Mechanical Engineering

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

11 Scopus citations

Abstract

In this paper, adaptive neural control is investigated for a class of unknown nonlinear systems in pure-feedback form with the generalized Prandtl-Ishlinskii hysteresis input. The non-affine problem both in the pure-feedback form and in the generalized Prandtl-Ishlinskii hysteresis input function is solved by adopting the Mean Value Theorem. By utilizing Lyapunov synthesis, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded (SGUUB), and the tracking error converges to a small neighborhood of zero. Simulation results are provided to illustrate the performance of the proposed approach.

Original language	English
Title of host publication	Proceedings of the 47th IEEE Conference on Decision and Control, CDC 2008
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	86-91
Number of pages	6
ISBN (Print)	9781424431243
DOIs	https://doi.org/10.1109/CDC.2008.4739240
State	Published - 2008
Event	47th IEEE Conference on Decision and Control, CDC 2008 - Cancun, Mexico Duration: Dec 9 2008 → Dec 11 2008

Publication series

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

Conference

Conference	47th IEEE Conference on Decision and Control, CDC 2008
Country/Territory	Mexico
City	Cancun
Period	12/9/08 → 12/11/08

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10.1109/CDC.2008.4739240

Cite this

Ren, B., Ge, S. S., Lee, T. H., & Su, C. Y. (2008). Adaptive neural control for uncertain nonlinear systems in pure-feedback form with hysteresis input. In Proceedings of the 47th IEEE Conference on Decision and Control, CDC 2008 (pp. 86-91). Article 4739240 (Proceedings of the IEEE Conference on Decision and Control). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2008.4739240

@inproceedings{207f5b888182414d95608244b45f5c86,

title = "Adaptive neural control for uncertain nonlinear systems in pure-feedback form with hysteresis input",

abstract = "In this paper, adaptive neural control is investigated for a class of unknown nonlinear systems in pure-feedback form with the generalized Prandtl-Ishlinskii hysteresis input. The non-affine problem both in the pure-feedback form and in the generalized Prandtl-Ishlinskii hysteresis input function is solved by adopting the Mean Value Theorem. By utilizing Lyapunov synthesis, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded (SGUUB), and the tracking error converges to a small neighborhood of zero. Simulation results are provided to illustrate the performance of the proposed approach.",

author = "Beibei Ren and Ge, {Shuzhi Sam} and Lee, {Tong Heng} and Su, {Chun Yi}",

year = "2008",

doi = "10.1109/CDC.2008.4739240",

language = "English",

isbn = "9781424431243",

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

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

pages = "86--91",

booktitle = "Proceedings of the 47th IEEE Conference on Decision and Control, CDC 2008",

note = "47th IEEE Conference on Decision and Control, CDC 2008 ; Conference date: 09-12-2008 Through 11-12-2008",

}

Ren, B, Ge, SS, Lee, TH & Su, CY 2008, Adaptive neural control for uncertain nonlinear systems in pure-feedback form with hysteresis input. in Proceedings of the 47th IEEE Conference on Decision and Control, CDC 2008., 4739240, Proceedings of the IEEE Conference on Decision and Control, Institute of Electrical and Electronics Engineers Inc., pp. 86-91, 47th IEEE Conference on Decision and Control, CDC 2008, Cancun, Mexico, 12/9/08. https://doi.org/10.1109/CDC.2008.4739240

Adaptive neural control for uncertain nonlinear systems in pure-feedback form with hysteresis input. / Ren, Beibei; Ge, Shuzhi Sam; Lee, Tong Heng et al.
Proceedings of the 47th IEEE Conference on Decision and Control, CDC 2008. Institute of Electrical and Electronics Engineers Inc., 2008. p. 86-91 4739240 (Proceedings of the IEEE Conference on Decision and Control).

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

TY - GEN

T1 - Adaptive neural control for uncertain nonlinear systems in pure-feedback form with hysteresis input

AU - Ren, Beibei

AU - Ge, Shuzhi Sam

AU - Lee, Tong Heng

AU - Su, Chun Yi

PY - 2008

Y1 - 2008

N2 - In this paper, adaptive neural control is investigated for a class of unknown nonlinear systems in pure-feedback form with the generalized Prandtl-Ishlinskii hysteresis input. The non-affine problem both in the pure-feedback form and in the generalized Prandtl-Ishlinskii hysteresis input function is solved by adopting the Mean Value Theorem. By utilizing Lyapunov synthesis, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded (SGUUB), and the tracking error converges to a small neighborhood of zero. Simulation results are provided to illustrate the performance of the proposed approach.

AB - In this paper, adaptive neural control is investigated for a class of unknown nonlinear systems in pure-feedback form with the generalized Prandtl-Ishlinskii hysteresis input. The non-affine problem both in the pure-feedback form and in the generalized Prandtl-Ishlinskii hysteresis input function is solved by adopting the Mean Value Theorem. By utilizing Lyapunov synthesis, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded (SGUUB), and the tracking error converges to a small neighborhood of zero. Simulation results are provided to illustrate the performance of the proposed approach.

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U2 - 10.1109/CDC.2008.4739240

DO - 10.1109/CDC.2008.4739240

M3 - Conference contribution

AN - SCOPUS:62949248523

SN - 9781424431243

T3 - Proceedings of the IEEE Conference on Decision and Control

SP - 86

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BT - Proceedings of the 47th IEEE Conference on Decision and Control, CDC 2008

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 47th IEEE Conference on Decision and Control, CDC 2008

Y2 - 9 December 2008 through 11 December 2008

ER -

Ren B, Ge SS, Lee TH, Su CY. Adaptive neural control for uncertain nonlinear systems in pure-feedback form with hysteresis input. In Proceedings of the 47th IEEE Conference on Decision and Control, CDC 2008. Institute of Electrical and Electronics Engineers Inc. 2008. p. 86-91. 4739240. (Proceedings of the IEEE Conference on Decision and Control). doi: 10.1109/CDC.2008.4739240

Adaptive neural control for uncertain nonlinear systems in pure-feedback form with hysteresis input

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