A behavioral approach to data-driven control with noisy input-output data Article Swipe
YOU?
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· 2022
· Open Access
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· DOI: https://doi.org/10.48550/arxiv.2206.08408
This paper deals with data-driven stability analysis and feedback stabillization of linear input-output systems in autoregressive (AR) form. We assume that noisy input-output data on a finite time-interval have been obtained from some unknown AR system. Data-based tests are then developed to analyse whether the unknown system is stable, or to verify whether a stabilizing dynamic feedback controller exists. If so, stabilizing controllers are computed using the data. In order to do this, we employ the behavioral approach to systems and control, meaning a departure from existing methods in data driven control. Our results heavily rely on a characterization of asymptotic stability of systems in AR form using the notion of quadratic difference form (QDF) as a natural framework for Lyapunov functions of autonomous AR systems. We introduce the concepts of informative data for quadratic stability and quadratic stabilization in the context of input-output AR systems and establish necessary and sufficient conditions for these properties to hold. In addition, this paper will build on results on quadratic matrix inequalties (QMIs) and a matrix version of Yakubovich's S-lemma.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2206.08408
- https://arxiv.org/pdf/2206.08408
- OA Status
- green
- Cited By
- 2
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4283207516
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4283207516Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2206.08408Digital Object Identifier
- Title
-
A behavioral approach to data-driven control with noisy input-output dataWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-06-16Full publication date if available
- Authors
-
Henk J. van Waarde, Jaap Eising, M. Kanat Camlibel, Harry L. TrentelmanList of authors in order
- Landing page
-
https://arxiv.org/abs/2206.08408Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2206.08408Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2206.08408Direct OA link when available
- Concepts
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Control theory (sociology), Context (archaeology), Stability (learning theory), Autoregressive model, Controller (irrigation), Computer science, Quadratic equation, Lemma (botany), Lyapunov function, Matrix (chemical analysis), Linear system, Mathematics, Control (management), Artificial intelligence, Machine learning, Statistics, Mathematical analysis, Physics, Quantum mechanics, Composite material, Nonlinear system, Geometry, Biology, Agronomy, Materials science, Paleontology, Poaceae, EcologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2023: 2Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.This | 0 |
| abstract_inverted_index.been | 29 |
| abstract_inverted_index.data | 23, 89, 132 |
| abstract_inverted_index.form | 106, 113 |
| abstract_inverted_index.from | 31, 85 |
| abstract_inverted_index.have | 28 |
| abstract_inverted_index.rely | 95 |
| abstract_inverted_index.some | 32 |
| abstract_inverted_index.that | 20 |
| abstract_inverted_index.then | 39 |
| abstract_inverted_index.this | 159 |
| abstract_inverted_index.will | 161 |
| abstract_inverted_index.with | 3 |
| abstract_inverted_index.(QDF) | 114 |
| abstract_inverted_index.build | 162 |
| abstract_inverted_index.data. | 67 |
| abstract_inverted_index.deals | 2 |
| abstract_inverted_index.form. | 17 |
| abstract_inverted_index.hold. | 156 |
| abstract_inverted_index.noisy | 21 |
| abstract_inverted_index.order | 69 |
| abstract_inverted_index.paper | 1, 160 |
| abstract_inverted_index.tests | 37 |
| abstract_inverted_index.these | 153 |
| abstract_inverted_index.this, | 72 |
| abstract_inverted_index.using | 65, 107 |
| abstract_inverted_index.(QMIs) | 169 |
| abstract_inverted_index.assume | 19 |
| abstract_inverted_index.driven | 90 |
| abstract_inverted_index.employ | 74 |
| abstract_inverted_index.finite | 26 |
| abstract_inverted_index.linear | 11 |
| abstract_inverted_index.matrix | 167, 172 |
| abstract_inverted_index.notion | 109 |
| abstract_inverted_index.system | 46 |
| abstract_inverted_index.verify | 51 |
| abstract_inverted_index.analyse | 42 |
| abstract_inverted_index.context | 141 |
| abstract_inverted_index.dynamic | 55 |
| abstract_inverted_index.exists. | 58 |
| abstract_inverted_index.heavily | 94 |
| abstract_inverted_index.meaning | 82 |
| abstract_inverted_index.methods | 87 |
| abstract_inverted_index.natural | 117 |
| abstract_inverted_index.results | 93, 164 |
| abstract_inverted_index.stable, | 48 |
| abstract_inverted_index.system. | 35 |
| abstract_inverted_index.systems | 13, 79, 103, 145 |
| abstract_inverted_index.unknown | 33, 45 |
| abstract_inverted_index.version | 173 |
| abstract_inverted_index.whether | 43, 52 |
| abstract_inverted_index.Lyapunov | 120 |
| abstract_inverted_index.S-lemma. | 176 |
| abstract_inverted_index.analysis | 6 |
| abstract_inverted_index.approach | 77 |
| abstract_inverted_index.computed | 64 |
| abstract_inverted_index.concepts | 129 |
| abstract_inverted_index.control, | 81 |
| abstract_inverted_index.control. | 91 |
| abstract_inverted_index.existing | 86 |
| abstract_inverted_index.feedback | 8, 56 |
| abstract_inverted_index.obtained | 30 |
| abstract_inverted_index.systems. | 125 |
| abstract_inverted_index.addition, | 158 |
| abstract_inverted_index.departure | 84 |
| abstract_inverted_index.developed | 40 |
| abstract_inverted_index.establish | 147 |
| abstract_inverted_index.framework | 118 |
| abstract_inverted_index.functions | 121 |
| abstract_inverted_index.introduce | 127 |
| abstract_inverted_index.necessary | 148 |
| abstract_inverted_index.quadratic | 111, 134, 137, 166 |
| abstract_inverted_index.stability | 5, 101, 135 |
| abstract_inverted_index.Data-based | 36 |
| abstract_inverted_index.asymptotic | 100 |
| abstract_inverted_index.autonomous | 123 |
| abstract_inverted_index.behavioral | 76 |
| abstract_inverted_index.conditions | 151 |
| abstract_inverted_index.controller | 57 |
| abstract_inverted_index.difference | 112 |
| abstract_inverted_index.properties | 154 |
| abstract_inverted_index.sufficient | 150 |
| abstract_inverted_index.controllers | 62 |
| abstract_inverted_index.data-driven | 4 |
| abstract_inverted_index.inequalties | 168 |
| abstract_inverted_index.informative | 131 |
| abstract_inverted_index.stabilizing | 54, 61 |
| abstract_inverted_index.Yakubovich's | 175 |
| abstract_inverted_index.input-output | 12, 22, 143 |
| abstract_inverted_index.stabilization | 138 |
| abstract_inverted_index.time-interval | 27 |
| abstract_inverted_index.autoregressive | 15 |
| abstract_inverted_index.stabillization | 9 |
| abstract_inverted_index.characterization | 98 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile |