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Parametric Continuo...
Parametric Continuous-Time Blind System Identification
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- Elton, Augustus (author)
- College of Engineering, Science and Environment, University of Newcastle, Callaghan, NSW, Australia
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- González, Rodrigo A. (author)
- Eindhoven University of Technology, Department of Mechanical Engineering, Eindhoven, The Netherlands
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- Welsh, James S. (author)
- College of Engineering, Science and Environment, University of Newcastle, Callaghan, NSW, Australia
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- Rojas, Cristian R., 1980- (author)
- KTH,Reglerteknik
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- Fu, Minyue (author)
- College of Engineering, Science and Environment, University of Newcastle, Callaghan, NSW, Australia
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(creator_code:org_t)
- Institute of Electrical and Electronics Engineers (IEEE), 2023
- 2023
- English.
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In: 2023 62nd IEEE Conference on Decision and Control, CDC2023. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1474-1479
- Related links:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- In this paper, the blind system identification problem for continuous-time systems is considered. A direct continuous-time estimator is proposed by utilising a state-variable-filter least squares approach. In the proposed method, coupled terms between the numerator polynomial of the system and input parameters appear in the parameter vector which are subsequently separated using a rank-1 approximation. An algorithm is then provided for the direct identification of a single-input single-output linear time-invariant continuous-time system which is shown to satisfy the property of correctness under some mild conditions. Monte Carlo simulations demonstrate the performance of the algorithm and verify that a model and input signal can be estimated to a proportion of their true values.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
Publication and Content Type
- ref (subject category)
- kon (subject category)
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