Data Informativity for Analysis of Linear Systems With Convex Conic Constraints Article Swipe
Jaap Eising
,
M. Kanat Camlibel
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1109/lcsys.2021.3077367
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1109/lcsys.2021.3077367
This paper studies the informativity problem for reachability and null-controllability of constrained systems. To be precise, we will focus on an unknown linear systems with convex conic constraints from which we measure data consisting of exact state trajectories of finite length. We are interested in performing system analysis of such an unknown system on the basis of the measured data. However, from such measurements it is only possible to obtain a unique system explaining the data in very restrictive cases. This means that we can not approach this problem using system identification combined with model based analysis. As such, we will formulate conditions on the data under which any such system consistent with the measurements is guaranteed to be reachable or null-controllable. These conditions are stated in terms of spectral conditions and subspace inclusions, and therefore they are easy to verify.
Related Topics
Concepts
Controllability
Conic section
Subspace topology
Null (SQL)
Reachability
Linear system
Regular polygon
Conic optimization
Measure (data warehouse)
Computer science
Focus (optics)
Mathematical optimization
Mathematics
System identification
Convex optimization
Linear subspace
Algorithm
Convex analysis
Applied mathematics
Artificial intelligence
Data mining
Pure mathematics
Mathematical analysis
Geometry
Optics
Physics
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1109/lcsys.2021.3077367
- OA Status
- green
- References
- 30
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W3135494422
All OpenAlex metadata
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- OpenAlex ID
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https://openalex.org/W3135494422Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/lcsys.2021.3077367Digital Object Identifier
- Title
-
Data Informativity for Analysis of Linear Systems With Convex Conic ConstraintsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-05-04Full publication date if available
- Authors
-
Jaap Eising, M. Kanat CamlibelList of authors in order
- Landing page
-
https://doi.org/10.1109/lcsys.2021.3077367Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2103.02430.pdfDirect OA link when available
- Concepts
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Controllability, Conic section, Subspace topology, Null (SQL), Reachability, Linear system, Regular polygon, Conic optimization, Measure (data warehouse), Computer science, Focus (optics), Mathematical optimization, Mathematics, System identification, Convex optimization, Linear subspace, Algorithm, Convex analysis, Applied mathematics, Artificial intelligence, Data mining, Pure mathematics, Mathematical analysis, Geometry, Optics, PhysicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
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30Number of works referenced by this work
- Related works (count)
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20Other works algorithmically related by OpenAlex
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