Adaptive Estimation for Uncertain Nonlinear Systems: A Sliding-Mode Observer Approach

R. Franco; H. Rios; D. Efimov; W. Perruquetti

doi:10.1109/CDC.2018.8619104

Adaptive Estimation for Uncertain Nonlinear Systems: A Sliding-Mode Observer Approach

R. Franco, H. Rios, D. Efimov, W. Perruquetti

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

2 Scopus citations

Abstract

This paper deals with the problem of adaptive estimation, i.e. the simultaneous estimation of the state and parameters, for a class of uncertain nonlinear systems. A nonlinear adaptive sliding-mode observer is proposed based on a nonlinear parameter estimation algorithm. The nonlinear parameter estimation algorithm provides a rate of convergence faster than exponential while the sliding-mode observer ensures ultimate boundness for the state estimation error attenuating the effects of the external disturbances. Linear matrix inequalities (LMIs) are provided for the synthesis of the adaptive observer and some simulation results show the feasibility of the proposed approach.

Original language	English
Title of host publication	2018 IEEE Conference on Decision and Control, CDC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	5506-5511
Number of pages	6
ISBN (Electronic)	9781538613955
DOIs	https://doi.org/10.1109/CDC.2018.8619104
State	Published - 2 Jul 2018
Event	57th IEEE Conference on Decision and Control, CDC 2018 - Miami, United States Duration: 17 Dec 2018 → 19 Dec 2018

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
Volume	2018-December
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	57th IEEE Conference on Decision and Control, CDC 2018
Country/Territory	United States
City	Miami
Period	17/12/18 → 19/12/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

Adaptive Observer
Nonlinear Systems
Sliding-Modes

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10.1109/CDC.2018.8619104

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Franco, R., Rios, H., Efimov, D., & Perruquetti, W. (2018). Adaptive Estimation for Uncertain Nonlinear Systems: A Sliding-Mode Observer Approach. In 2018 IEEE Conference on Decision and Control, CDC 2018 (pp. 5506-5511). Article 8619104 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2018-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2018.8619104

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title = "Adaptive Estimation for Uncertain Nonlinear Systems: A Sliding-Mode Observer Approach",

abstract = "This paper deals with the problem of adaptive estimation, i.e. the simultaneous estimation of the state and parameters, for a class of uncertain nonlinear systems. A nonlinear adaptive sliding-mode observer is proposed based on a nonlinear parameter estimation algorithm. The nonlinear parameter estimation algorithm provides a rate of convergence faster than exponential while the sliding-mode observer ensures ultimate boundness for the state estimation error attenuating the effects of the external disturbances. Linear matrix inequalities (LMIs) are provided for the synthesis of the adaptive observer and some simulation results show the feasibility of the proposed approach.",

keywords = "Adaptive Observer, Nonlinear Systems, Sliding-Modes",

author = "R. Franco and H. Rios and D. Efimov and W. Perruquetti",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 57th IEEE Conference on Decision and Control, CDC 2018 ; Conference date: 17-12-2018 Through 19-12-2018",

year = "2018",

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day = "2",

doi = "10.1109/CDC.2018.8619104",

language = "Ingl{\'e}s",

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

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Franco, R, Rios, H, Efimov, D & Perruquetti, W 2018, Adaptive Estimation for Uncertain Nonlinear Systems: A Sliding-Mode Observer Approach. in 2018 IEEE Conference on Decision and Control, CDC 2018., 8619104, Proceedings of the IEEE Conference on Decision and Control, vol. 2018-December, Institute of Electrical and Electronics Engineers Inc., pp. 5506-5511, 57th IEEE Conference on Decision and Control, CDC 2018, Miami, United States, 17/12/18. https://doi.org/10.1109/CDC.2018.8619104

Adaptive Estimation for Uncertain Nonlinear Systems: A Sliding-Mode Observer Approach. / Franco, R.; Rios, H.; Efimov, D. et al.
2018 IEEE Conference on Decision and Control, CDC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 5506-5511 8619104 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2018-December).

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

TY - GEN

T1 - Adaptive Estimation for Uncertain Nonlinear Systems

T2 - 57th IEEE Conference on Decision and Control, CDC 2018

AU - Franco, R.

AU - Rios, H.

AU - Efimov, D.

AU - Perruquetti, W.

PY - 2018/7/2

Y1 - 2018/7/2

N2 - This paper deals with the problem of adaptive estimation, i.e. the simultaneous estimation of the state and parameters, for a class of uncertain nonlinear systems. A nonlinear adaptive sliding-mode observer is proposed based on a nonlinear parameter estimation algorithm. The nonlinear parameter estimation algorithm provides a rate of convergence faster than exponential while the sliding-mode observer ensures ultimate boundness for the state estimation error attenuating the effects of the external disturbances. Linear matrix inequalities (LMIs) are provided for the synthesis of the adaptive observer and some simulation results show the feasibility of the proposed approach.

AB - This paper deals with the problem of adaptive estimation, i.e. the simultaneous estimation of the state and parameters, for a class of uncertain nonlinear systems. A nonlinear adaptive sliding-mode observer is proposed based on a nonlinear parameter estimation algorithm. The nonlinear parameter estimation algorithm provides a rate of convergence faster than exponential while the sliding-mode observer ensures ultimate boundness for the state estimation error attenuating the effects of the external disturbances. Linear matrix inequalities (LMIs) are provided for the synthesis of the adaptive observer and some simulation results show the feasibility of the proposed approach.

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KW - Nonlinear Systems

KW - Sliding-Modes

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U2 - 10.1109/CDC.2018.8619104

DO - 10.1109/CDC.2018.8619104

M3 - Contribución a la conferencia

AN - SCOPUS:85062172602

T3 - Proceedings of the IEEE Conference on Decision and Control

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EP - 5511

BT - 2018 IEEE Conference on Decision and Control, CDC 2018

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 17 December 2018 through 19 December 2018

ER -

Adaptive Estimation for Uncertain Nonlinear Systems: A Sliding-Mode Observer Approach

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