Identification of Additive Continuous-time Systems in Open and Closed loop Article Swipe

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Rodrigo A. González , Koen Classens , Cristian R. Rojas , James S. Welsh , Tom Oomen ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2401.01263

When identifying electrical, mechanical, or biological systems, parametric continuous-time identification methods can lead to interpretable and parsimonious models when the model structure aligns with the physical properties of the system. Traditional linear system identification may not consider the most parsimonious model when relying solely on unfactored transfer functions, which typically result from standard direct approaches. This paper presents a novel identification method that delivers additive models for both open and closed-loop setups. The estimators that are derived are shown to be generically consistent, and can admit the identification of marginally stable additive systems. Numerical simulations show the efficacy of the proposed approach, and its performance in identifying a modal representation of a flexible beam is verified using experimental data.

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Identification (biology) Modal Estimator System identification Representation (politics) Computer science Transfer function Parametric statistics Closed loop Parametric model Control theory (sociology) Mathematics Control engineering Data mining Artificial intelligence Engineering Control (management) Measure (data warehouse) Statistics Political science Law Electrical engineering Botany Chemistry Biology Politics Polymer chemistry

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2401.01263
PDF: https://arxiv.org/pdf/2401.01263
OA Status: green
Cited By: 1
Related Works: 10
OpenAlex ID: https://openalex.org/W4390572835

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DOI: https://doi.org/10.48550/arxiv.2401.01263

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Title: Identification of Additive Continuous-time Systems in Open and Closed loop

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Type: preprint

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Language: en

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Publication year: 2024

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Publication date: 2024-01-02

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Authors: Rodrigo A. González, Koen Classens, Cristian R. Rojas, James S. Welsh, Tom Oomen

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Landing page: https://arxiv.org/abs/2401.01263

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PDF URL: https://arxiv.org/pdf/2401.01263

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Concepts: Identification (biology), Modal, Estimator, System identification, Representation (politics), Computer science, Transfer function, Parametric statistics, Closed loop, Parametric model, Control theory (sociology), Mathematics, Control engineering, Data mining, Artificial intelligence, Engineering, Control (management), Measure (data warehouse), Statistics, Political science, Law, Electrical engineering, Botany, Chemistry, Biology, Politics, Polymer chemistry

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Cited by: 1

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abstract_inverted_index.Numerical	93
abstract_inverted_index.approach,	101
abstract_inverted_index.structure	21
abstract_inverted_index.typically	49
abstract_inverted_index.biological	5
abstract_inverted_index.estimators	73
abstract_inverted_index.functions,	47
abstract_inverted_index.marginally	89
abstract_inverted_index.parametric	7
abstract_inverted_index.properties	26
abstract_inverted_index.unfactored	45
abstract_inverted_index.Traditional	30
abstract_inverted_index.approaches.	54
abstract_inverted_index.closed-loop	70
abstract_inverted_index.consistent,	82
abstract_inverted_index.electrical,	2
abstract_inverted_index.generically	81
abstract_inverted_index.identifying	1, 106
abstract_inverted_index.mechanical,	3
abstract_inverted_index.performance	104
abstract_inverted_index.simulations	94
abstract_inverted_index.experimental	117
abstract_inverted_index.parsimonious	16, 39
abstract_inverted_index.interpretable	14
abstract_inverted_index.identification	9, 33, 60, 87
abstract_inverted_index.representation	109
abstract_inverted_index.continuous-time	8
cited_by_percentile_year
countries_distinct_count	0
institutions_distinct_count	5
citation_normalized_percentile