Input design to maximize information for identification of MIMO systems

Kurt Erik Häggblom

Input design to maximize information for identification of MIMO systems

Kurt Erik Häggblom

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

2 Citations (Scopus)

12 Downloads (Pure)

Abstract

A new input design method for identification of multiple-input multiple-output (MIMO) systems is introduced. The method is completely data based as opposed to previous model-based methods. The data are obtained from one or more experiments with the system to be identified. These experiments do not require any MIMO input design. The design objective is to generate maximally informative data when a new experiment based on MIMO input design is done. The data are considered to be maximally informative when the outputs have maximal variance, subject to some constraints, and no correlation. Since the input design, with given type of perturbation signal, is not unique, it is possible to optimize some additional property, such as minimization of input or output peak value. The various design options are illustrated by application to a system with three inputs and three outputs.

Original language	Undefined/Unknown
Title of host publication	2019 12th Asian control conference (ASCC)
Publisher	IEEE
Pages	1323–1328
ISBN (Electronic)	978-4-88898-300-6
ISBN (Print)	978-1-7281-0263-4
Publication status	Published - 2019
MoE publication type	A4 Article in a conference publication
Event	Asian Control Conference - 12th Asian Control Conference (ASCC 2019) Duration: 9 Jun 2019 → 12 Jun 2019

Conference

Conference	Asian Control Conference
Period	09/06/19 → 12/06/19

Keywords

data-based design
experiment design
ill-conditioned systems
multivariable systems
system identification

Access to Document

HaggblomFin.pdfAccepted author manuscript, 261 KBLicence: Publisher rights policy

Cite this

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title = "Input design to maximize information for identification of MIMO systems",

abstract = "A new input design method for identification of multiple-input multiple-output (MIMO) systems is introduced. The method is completely data based as opposed to previous model-based methods. The data are obtained from one or more experiments with the system to be identified. These experiments do not require any MIMO input design. The design objective is to generate maximally informative data when a new experiment based on MIMO input design is done. The data are considered to be maximally informative when the outputs have maximal variance, subject to some constraints, and no correlation. Since the input design, with given type of perturbation signal, is not unique, it is possible to optimize some additional property, such as minimization of input or output peak value. The various design options are illustrated by application to a system with three inputs and three outputs.",

keywords = "data-based design, experiment design, ill-conditioned systems, multivariable systems, system identification, data-based design, experiment design, ill-conditioned systems, multivariable systems, system identification, data-based design, experiment design, ill-conditioned systems, multivariable systems, system identification",

author = "H{\"a}ggblom, {Kurt Erik}",

note = "rt. Date Added to IEEE Xplore: 18 July 2019 USB ISBN: 978-4-88898-301-3 https://conferences.ieeeauthorcenter.ieee.org/get-published/post-your-paper/ Authors may share or post their accepted paper 24 months embargo “{\textcopyright} 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.” ------------------------------------------------------------ Har kontaktat kurt-erik.haggblom@abo.fi den 26.2.2020/LN ------------------------------------------------------------; Asian Control Conference ; Conference date: 09-06-2019 Through 12-06-2019",

year = "2019",

language = "Odefinierat/ok{\"a}nt",

isbn = "978-1-7281-0263-4",

pages = "1323–1328",

booktitle = "2019 12th Asian control conference (ASCC)",

publisher = "IEEE",

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AU - Häggblom, Kurt Erik

N1 - rt. Date Added to IEEE Xplore: 18 July 2019 USB ISBN: 978-4-88898-301-3 https://conferences.ieeeauthorcenter.ieee.org/get-published/post-your-paper/ Authors may share or post their accepted paper 24 months embargo “© 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.” ------------------------------------------------------------ Har kontaktat kurt-erik.haggblom@abo.fi den 26.2.2020/LN ------------------------------------------------------------

PY - 2019

Y1 - 2019

N2 - A new input design method for identification of multiple-input multiple-output (MIMO) systems is introduced. The method is completely data based as opposed to previous model-based methods. The data are obtained from one or more experiments with the system to be identified. These experiments do not require any MIMO input design. The design objective is to generate maximally informative data when a new experiment based on MIMO input design is done. The data are considered to be maximally informative when the outputs have maximal variance, subject to some constraints, and no correlation. Since the input design, with given type of perturbation signal, is not unique, it is possible to optimize some additional property, such as minimization of input or output peak value. The various design options are illustrated by application to a system with three inputs and three outputs.

AB - A new input design method for identification of multiple-input multiple-output (MIMO) systems is introduced. The method is completely data based as opposed to previous model-based methods. The data are obtained from one or more experiments with the system to be identified. These experiments do not require any MIMO input design. The design objective is to generate maximally informative data when a new experiment based on MIMO input design is done. The data are considered to be maximally informative when the outputs have maximal variance, subject to some constraints, and no correlation. Since the input design, with given type of perturbation signal, is not unique, it is possible to optimize some additional property, such as minimization of input or output peak value. The various design options are illustrated by application to a system with three inputs and three outputs.

KW - data-based design

KW - experiment design

KW - ill-conditioned systems

KW - multivariable systems

KW - system identification

KW - data-based design

KW - experiment design

KW - ill-conditioned systems

KW - multivariable systems

KW - system identification

KW - data-based design

KW - experiment design

KW - ill-conditioned systems

KW - multivariable systems

KW - system identification

M3 - Konferensbidrag

SN - 978-1-7281-0263-4

SP - 1323

EP - 1328

BT - 2019 12th Asian control conference (ASCC)

PB - IEEE

T2 - Asian Control Conference

Y2 - 9 June 2019 through 12 June 2019

ER -