Data-driven input design to maximize information in MIMO system identification

Kurt Erik Häggblom

Data-driven input design to maximize information in MIMO system identification

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

Original language	Undefined/Unknown
Title of host publication	2019 AIChE annual meeting
Publisher	American Institute of Chemical Engineers
Pages	–
ISBN (Print)	978-0-8169-1112-7
Publication status	Published - 2019
MoE publication type	A4 Article in a conference publication
Event	Annual meeting of the American Institute of Chemical Engineers - 2019 AIChE Annual Meeting Duration: 10 Nov 2019 → 15 Nov 2019

Conference

Conference	Annual meeting of the American Institute of Chemical Engineers
Period	10/11/19 → 15/11/19

Keywords

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

Access to Document

https://www.aiche.org/conferences/aiche-annual-meeting/2019/proceeding/paper/324c-data-driven-input-design-maximize-information-mimo-system-identification

Cite this

@inproceedings{e21b2a25b0484be78c3b53b4d958b291,

title = "Data-driven input design to maximize information in MIMO system identification",

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 = "”Copyright to this paper is retained by the author(s)”. KEH har skickat in en l{\"a}ngre text som kommer ut i IEEE Transactions on Industrial Informatics, s{\aa} l{\"a}nka INTE till denna h{\"a}r. (Spara f{\"o}r n{\"a}sta {\aa}rs rapportering) https://aiche.confex.com/data/extendedabstract/aiche/2019/Paper_571979_extendedabstract_20423_0.pdf; Annual meeting of the American Institute of Chemical Engineers ; Conference date: 10-11-2019 Through 15-11-2019",

year = "2019",

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

isbn = "978-0-8169-1112-7",

pages = "–",

booktitle = "2019 AIChE annual meeting",

publisher = "American Institute of Chemical Engineers",

}

Häggblom, KE 2019, Data-driven input design to maximize information in MIMO system identification. in 2019 AIChE annual meeting. American Institute of Chemical Engineers, pp. –, Annual meeting of the American Institute of Chemical Engineers, 10/11/19. <https://www.aiche.org/conferences/aiche-annual-meeting/2019/proceeding/paper/324c-data-driven-input-design-maximize-information-mimo-system-identification>

TY - GEN

T1 - Data-driven input design to maximize information in MIMO system identification

AU - Häggblom, Kurt Erik

N1 - ”Copyright to this paper is retained by the author(s)”. KEH har skickat in en längre text som kommer ut i IEEE Transactions on Industrial Informatics, så länka INTE till denna här. (Spara för nästa års rapportering) https://aiche.confex.com/data/extendedabstract/aiche/2019/Paper_571979_extendedabstract_20423_0.pdf

PY - 2019

Y1 - 2019

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 - 978-0-8169-1112-7

SP - –

BT - 2019 AIChE annual meeting

PB - American Institute of Chemical Engineers

T2 - Annual meeting of the American Institute of Chemical Engineers

Y2 - 10 November 2019 through 15 November 2019

ER -