Data-Based Modeling and Control of Dynamical Systems: Parameter Estimation

Damien Gueho; Manoranjan Majji; Puneet Singla

doi:10.1109/CDC45484.2021.9682951

Data-Based Modeling and Control of Dynamical Systems: Parameter Estimation

Damien Gueho, Manoranjan Majji, Puneet Singla

Aerospace Engineering

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

1 Scopus citations

Abstract

Parameter estimation methods to provide data-based models to control complex dynamical systems are reviewed. Starting from least square minimization of the equation error, the tutorial provides an overview of how different perspectives of parameter estimation lead to various algorithms that are used in diverse contexts. Both statistical and deterministic approaches are discussed, and the utility of model inferences are explained. The discussions provide a context and review relevant background with respect to three application papers involving recent advances in Gaussian Process Regression (GPR), state estimation approaches and data-driven modeling.

Original language	English (US)
Title of host publication	60th IEEE Conference on Decision and Control, CDC 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	31-36
Number of pages	6
ISBN (Electronic)	9781665436595
DOIs	https://doi.org/10.1109/CDC45484.2021.9682951
State	Published - 2021
Event	60th IEEE Conference on Decision and Control, CDC 2021 - Austin, United States Duration: Dec 13 2021 → Dec 17 2021

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
Volume	2021-December
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	60th IEEE Conference on Decision and Control, CDC 2021
Country/Territory	United States
City	Austin
Period	12/13/21 → 12/17/21

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Modeling and Simulation
Control and Optimization

Access to Document

10.1109/CDC45484.2021.9682951

Cite this

Gueho, D., Majji, M., & Singla, P. (2021). Data-Based Modeling and Control of Dynamical Systems: Parameter Estimation. In 60th IEEE Conference on Decision and Control, CDC 2021 (pp. 31-36). (Proceedings of the IEEE Conference on Decision and Control; Vol. 2021-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC45484.2021.9682951

@inproceedings{9b7e07497cd947169332e4d7aaea8136,

title = "Data-Based Modeling and Control of Dynamical Systems: Parameter Estimation",

abstract = "Parameter estimation methods to provide data-based models to control complex dynamical systems are reviewed. Starting from least square minimization of the equation error, the tutorial provides an overview of how different perspectives of parameter estimation lead to various algorithms that are used in diverse contexts. Both statistical and deterministic approaches are discussed, and the utility of model inferences are explained. The discussions provide a context and review relevant background with respect to three application papers involving recent advances in Gaussian Process Regression (GPR), state estimation approaches and data-driven modeling.",

author = "Damien Gueho and Manoranjan Majji and Puneet Singla",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 60th IEEE Conference on Decision and Control, CDC 2021 ; Conference date: 13-12-2021 Through 17-12-2021",

year = "2021",

doi = "10.1109/CDC45484.2021.9682951",

language = "English (US)",

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

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

pages = "31--36",

booktitle = "60th IEEE Conference on Decision and Control, CDC 2021",

address = "United States",

}

Gueho, D, Majji, M & Singla, P 2021, Data-Based Modeling and Control of Dynamical Systems: Parameter Estimation. in 60th IEEE Conference on Decision and Control, CDC 2021. Proceedings of the IEEE Conference on Decision and Control, vol. 2021-December, Institute of Electrical and Electronics Engineers Inc., pp. 31-36, 60th IEEE Conference on Decision and Control, CDC 2021, Austin, United States, 12/13/21. https://doi.org/10.1109/CDC45484.2021.9682951

Data-Based Modeling and Control of Dynamical Systems: Parameter Estimation. / Gueho, Damien; Majji, Manoranjan; Singla, Puneet.
60th IEEE Conference on Decision and Control, CDC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 31-36 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2021-December).

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

TY - GEN

T1 - Data-Based Modeling and Control of Dynamical Systems

T2 - 60th IEEE Conference on Decision and Control, CDC 2021

AU - Gueho, Damien

AU - Majji, Manoranjan

AU - Singla, Puneet

PY - 2021

Y1 - 2021

N2 - Parameter estimation methods to provide data-based models to control complex dynamical systems are reviewed. Starting from least square minimization of the equation error, the tutorial provides an overview of how different perspectives of parameter estimation lead to various algorithms that are used in diverse contexts. Both statistical and deterministic approaches are discussed, and the utility of model inferences are explained. The discussions provide a context and review relevant background with respect to three application papers involving recent advances in Gaussian Process Regression (GPR), state estimation approaches and data-driven modeling.

AB - Parameter estimation methods to provide data-based models to control complex dynamical systems are reviewed. Starting from least square minimization of the equation error, the tutorial provides an overview of how different perspectives of parameter estimation lead to various algorithms that are used in diverse contexts. Both statistical and deterministic approaches are discussed, and the utility of model inferences are explained. The discussions provide a context and review relevant background with respect to three application papers involving recent advances in Gaussian Process Regression (GPR), state estimation approaches and data-driven modeling.

UR - http://www.scopus.com/inward/record.url?scp=85126026860&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85126026860&partnerID=8YFLogxK

U2 - 10.1109/CDC45484.2021.9682951

DO - 10.1109/CDC45484.2021.9682951

M3 - Conference contribution

AN - SCOPUS:85126026860

T3 - Proceedings of the IEEE Conference on Decision and Control

SP - 31

EP - 36

BT - 60th IEEE Conference on Decision and Control, CDC 2021

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 13 December 2021 through 17 December 2021

ER -

Data-Based Modeling and Control of Dynamical Systems: Parameter Estimation

Abstract

Publication series

Conference

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this