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Informativity for identification for 2D state-representable autonomous systems, with applications to data-driven simulation

Informativity for identification for 2D state-representable autonomous systems, with applications to data-driven simulation
Informativity for identification for 2D state-representable autonomous systems, with applications to data-driven simulation
We define persistency of excitation and informativity for system identification for the class of 2D state-representable autonomous systems. We characterize informativity for system identification in terms of properties of a matrix constructed from the restrictions of a system trajectory on successive consecutive lines. We state a procedure to compute arbitrary trajectories from a “sufficiently rich” one.
0743-1546
584-589
IEEE
Rapisarda, Paolo
79efc3b0-a7c6-4ca7-a7f8-de5770a4281b
Pal, Debasattam
4f59a013-2719-431f-9f3d-d3966d7ac34a
Rapisarda, Paolo
79efc3b0-a7c6-4ca7-a7f8-de5770a4281b
Pal, Debasattam
4f59a013-2719-431f-9f3d-d3966d7ac34a

Rapisarda, Paolo and Pal, Debasattam (2024) Informativity for identification for 2D state-representable autonomous systems, with applications to data-driven simulation. In 2023 62nd IEEE Conference on Decision and Control, CDC 2023. IEEE. pp. 584-589 . (doi:10.1109/CDC49753.2023.10383552).

Record type: Conference or Workshop Item (Paper)

Abstract

We define persistency of excitation and informativity for system identification for the class of 2D state-representable autonomous systems. We characterize informativity for system identification in terms of properties of a matrix constructed from the restrictions of a system trajectory on successive consecutive lines. We state a procedure to compute arbitrary trajectories from a “sufficiently rich” one.

Text
CDC23_0578_FI - Accepted Manuscript
Restricted to Repository staff only until 19 January 2026.
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More information

Accepted/In Press date: 2023
Published date: 19 January 2024
Additional Information: Publisher Copyright: © 2023 IEEE.
Venue - Dates: 62nd IEEE Conference on Decision and Control<br/>, , Singapore, 2023-12-13

Identifiers

Local EPrints ID: 486548
URI: http://eprints.soton.ac.uk/id/eprint/486548
ISSN: 0743-1546
PURE UUID: 5750c507-480f-4020-a1b4-7ca73c2b0feb

Catalogue record

Date deposited: 25 Jan 2024 17:35
Last modified: 15 Apr 2024 16:47

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Contributors

Author: Paolo Rapisarda
Author: Debasattam Pal

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