Multi-Objective Nonlinear Observer Design using BMIs

Yan Wang, Rajesh Rajamani, Ali Zemouche

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper applies a nonconvex bilinear matrix inequality (BMI) based approach to design a nonlinear observer that satisfies multiple performance criteria simultaneously. First, the feasibility analysis of the BMI constraint is transformed into an eigenvalue problem and the convex-concave based sequential LMI optimization method is applied to search for a feasible solution. Then, the design of the nonlinear observer is formulated as a BMI feasibility problem where the estimation error dynamics is transformed into a Lure system with a sector condition constructed from the element-wise bounds on the Jacobian matrix of the nonlinearities. Finally, a numerical example is presented to demonstrate the applicability of the proposed algorithm.

Original languageEnglish (US)
Title of host publication2018 Annual American Control Conference, ACC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1346-1351
Number of pages6
ISBN (Print)9781538654286
DOIs
StatePublished - Aug 9 2018
Event2018 Annual American Control Conference, ACC 2018 - Milwauke, United States
Duration: Jun 27 2018Jun 29 2018

Publication series

NameProceedings of the American Control Conference
Volume2018-June
ISSN (Print)0743-1619

Other

Other2018 Annual American Control Conference, ACC 2018
CountryUnited States
CityMilwauke
Period6/27/186/29/18

Fingerprint

Jacobian matrices
Error analysis

Cite this

Wang, Y., Rajamani, R., & Zemouche, A. (2018). Multi-Objective Nonlinear Observer Design using BMIs. In 2018 Annual American Control Conference, ACC 2018 (pp. 1346-1351). [8431383] (Proceedings of the American Control Conference; Vol. 2018-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ACC.2018.8431383

Multi-Objective Nonlinear Observer Design using BMIs. / Wang, Yan; Rajamani, Rajesh; Zemouche, Ali.

2018 Annual American Control Conference, ACC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1346-1351 8431383 (Proceedings of the American Control Conference; Vol. 2018-June).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wang, Y, Rajamani, R & Zemouche, A 2018, Multi-Objective Nonlinear Observer Design using BMIs. in 2018 Annual American Control Conference, ACC 2018., 8431383, Proceedings of the American Control Conference, vol. 2018-June, Institute of Electrical and Electronics Engineers Inc., pp. 1346-1351, 2018 Annual American Control Conference, ACC 2018, Milwauke, United States, 6/27/18. https://doi.org/10.23919/ACC.2018.8431383
Wang Y, Rajamani R, Zemouche A. Multi-Objective Nonlinear Observer Design using BMIs. In 2018 Annual American Control Conference, ACC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1346-1351. 8431383. (Proceedings of the American Control Conference). https://doi.org/10.23919/ACC.2018.8431383
Wang, Yan ; Rajamani, Rajesh ; Zemouche, Ali. / Multi-Objective Nonlinear Observer Design using BMIs. 2018 Annual American Control Conference, ACC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1346-1351 (Proceedings of the American Control Conference).
@inproceedings{46e9002ef2574dc9af41dbc60d08fb48,
title = "Multi-Objective Nonlinear Observer Design using BMIs",
abstract = "This paper applies a nonconvex bilinear matrix inequality (BMI) based approach to design a nonlinear observer that satisfies multiple performance criteria simultaneously. First, the feasibility analysis of the BMI constraint is transformed into an eigenvalue problem and the convex-concave based sequential LMI optimization method is applied to search for a feasible solution. Then, the design of the nonlinear observer is formulated as a BMI feasibility problem where the estimation error dynamics is transformed into a Lure system with a sector condition constructed from the element-wise bounds on the Jacobian matrix of the nonlinearities. Finally, a numerical example is presented to demonstrate the applicability of the proposed algorithm.",
author = "Yan Wang and Rajesh Rajamani and Ali Zemouche",
year = "2018",
month = "8",
day = "9",
doi = "10.23919/ACC.2018.8431383",
language = "English (US)",
isbn = "9781538654286",
series = "Proceedings of the American Control Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1346--1351",
booktitle = "2018 Annual American Control Conference, ACC 2018",

}

TY - GEN

T1 - Multi-Objective Nonlinear Observer Design using BMIs

AU - Wang, Yan

AU - Rajamani, Rajesh

AU - Zemouche, Ali

PY - 2018/8/9

Y1 - 2018/8/9

N2 - This paper applies a nonconvex bilinear matrix inequality (BMI) based approach to design a nonlinear observer that satisfies multiple performance criteria simultaneously. First, the feasibility analysis of the BMI constraint is transformed into an eigenvalue problem and the convex-concave based sequential LMI optimization method is applied to search for a feasible solution. Then, the design of the nonlinear observer is formulated as a BMI feasibility problem where the estimation error dynamics is transformed into a Lure system with a sector condition constructed from the element-wise bounds on the Jacobian matrix of the nonlinearities. Finally, a numerical example is presented to demonstrate the applicability of the proposed algorithm.

AB - This paper applies a nonconvex bilinear matrix inequality (BMI) based approach to design a nonlinear observer that satisfies multiple performance criteria simultaneously. First, the feasibility analysis of the BMI constraint is transformed into an eigenvalue problem and the convex-concave based sequential LMI optimization method is applied to search for a feasible solution. Then, the design of the nonlinear observer is formulated as a BMI feasibility problem where the estimation error dynamics is transformed into a Lure system with a sector condition constructed from the element-wise bounds on the Jacobian matrix of the nonlinearities. Finally, a numerical example is presented to demonstrate the applicability of the proposed algorithm.

UR - http://www.scopus.com/inward/record.url?scp=85052572974&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85052572974&partnerID=8YFLogxK

U2 - 10.23919/ACC.2018.8431383

DO - 10.23919/ACC.2018.8431383

M3 - Conference contribution

AN - SCOPUS:85052572974

SN - 9781538654286

T3 - Proceedings of the American Control Conference

SP - 1346

EP - 1351

BT - 2018 Annual American Control Conference, ACC 2018

PB - Institute of Electrical and Electronics Engineers Inc.

ER -