MPC based optimal input design for nonlinear system identification

Muhammad Zeeshan Babar; Marco Baglietto

doi:10.1109/ICSTCC.2016.7790735

MPC based optimal input design for nonlinear system identification

Muhammad Zeeshan Babar, Marco Baglietto

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

Abstract

A combined nonlinear model predictive control with extended Kalman filter strategy has been proposed for optimal input design. As the designed controller depend on the identified parameters, the achievable performance highly depends on the quality of the identified information. The degradation in achieving the desired control performance is quantified b y introducing an optimality criteria which minimize the error covariance matrix of the identified parameters. The major contribution is using the information of the system parameter at every sample time to improve the control performance at next time step. The the performance of the proposed algorithm is verified by numerical simulations for a example system.

Original language	English
Title of host publication	2016 20th International Conference on System Theory, Control and Computing (ICSTCC)
Editors	Emil Petre, Marius Brezovan
Publisher	IEEE
Pages	619-625
Number of pages	7
ISBN (Electronic)	978-1-5090-2720-0, 978-1-5090-2719-4
ISBN (Print)	978-1-5090-2721-7
DOIs	https://doi.org/10.1109/ICSTCC.2016.7790735
Publication status	Published - 19 Dec 2016
Event	2016 20th International Conference on System Theory, Control and Computing (ICSTCC) - Sinaia, Romania Duration: 13 Oct 2016 → 15 Oct 2016 Conference number: 20 http://ace.ucv.ro/icstcc2016/cfp.php

Conference

Conference	2016 20th International Conference on System Theory, Control and Computing (ICSTCC)
Abbreviated title	ICSTCC 2016
Country/Territory	Romania
City	Sinaia
Period	13/10/16 → 15/10/16
Internet address	http://ace.ucv.ro/icstcc2016/cfp.php

Keywords

Optimal Input
Model Predictive Control
Extended Kalman Filter
Active System Identification

Access to Document

10.1109/ICSTCC.2016.7790735Licence: All Rights Reserved

https://ieeexplore.ieee.org/abstract/document/7790735Licence: All Rights Reserved

Cite this

@inproceedings{29ca0b30349f4d4a8df9bc3bcf731b01,

title = "MPC based optimal input design for nonlinear system identification",

abstract = "A combined nonlinear model predictive control with extended Kalman filter strategy has been proposed for optimal input design. As the designed controller depend on the identified parameters, the achievable performance highly depends on the quality of the identified information. The degradation in achieving the desired control performance is quantified b y introducing an optimality criteria which minimize the error covariance matrix of the identified parameters. The major contribution is using the information of the system parameter at every sample time to improve the control performance at next time step. The the performance of the proposed algorithm is verified by numerical simulations for a example system.",

keywords = "Optimal Input, Model Predictive Control, Extended Kalman Filter, Active System Identification",

author = "Babar, {Muhammad Zeeshan} and Marco Baglietto",

year = "2016",

month = dec,

day = "19",

doi = "10.1109/ICSTCC.2016.7790735",

language = "English",

isbn = "978-1-5090-2721-7",

pages = "619--625",

editor = "Emil Petre and Marius Brezovan",

booktitle = "2016 20th International Conference on System Theory, Control and Computing (ICSTCC)",

publisher = "IEEE",

note = "2016 20th International Conference on System Theory, Control and Computing (ICSTCC)<br/>, ICSTCC 2016 ; Conference date: 13-10-2016 Through 15-10-2016",

url = "http://ace.ucv.ro/icstcc2016/cfp.php",

}

Babar, MZ & Baglietto, M 2016, MPC based optimal input design for nonlinear system identification. in E Petre & M Brezovan (eds), 2016 20th International Conference on System Theory, Control and Computing (ICSTCC). IEEE, pp. 619-625, 2016 20th International Conference on System Theory, Control and Computing (ICSTCC)
, Sinaia, Romania, 13/10/16. https://doi.org/10.1109/ICSTCC.2016.7790735

TY - GEN

T1 - MPC based optimal input design for nonlinear system identification

AU - Babar, Muhammad Zeeshan

AU - Baglietto, Marco

N1 - Conference code: 20

PY - 2016/12/19

Y1 - 2016/12/19

N2 - A combined nonlinear model predictive control with extended Kalman filter strategy has been proposed for optimal input design. As the designed controller depend on the identified parameters, the achievable performance highly depends on the quality of the identified information. The degradation in achieving the desired control performance is quantified b y introducing an optimality criteria which minimize the error covariance matrix of the identified parameters. The major contribution is using the information of the system parameter at every sample time to improve the control performance at next time step. The the performance of the proposed algorithm is verified by numerical simulations for a example system.

AB - A combined nonlinear model predictive control with extended Kalman filter strategy has been proposed for optimal input design. As the designed controller depend on the identified parameters, the achievable performance highly depends on the quality of the identified information. The degradation in achieving the desired control performance is quantified b y introducing an optimality criteria which minimize the error covariance matrix of the identified parameters. The major contribution is using the information of the system parameter at every sample time to improve the control performance at next time step. The the performance of the proposed algorithm is verified by numerical simulations for a example system.

KW - Optimal Input

KW - Model Predictive Control

KW - Extended Kalman Filter

KW - Active System Identification

U2 - 10.1109/ICSTCC.2016.7790735

DO - 10.1109/ICSTCC.2016.7790735

M3 - Conference contribution

SN - 978-1-5090-2721-7

SP - 619

EP - 625

BT - 2016 20th International Conference on System Theory, Control and Computing (ICSTCC)

A2 - Petre, Emil

A2 - Brezovan, Marius

PB - IEEE

T2 - 2016 20th International Conference on System Theory, Control and Computing (ICSTCC)<br/>

Y2 - 13 October 2016 through 15 October 2016

ER -

MPC based optimal input design for nonlinear system identification

Abstract

Conference

Keywords

Access to Document

Fingerprint

Cite this