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Finite‐time estimation for a class of systems with unknown time‐delay using modulating functions‐based method
Abstract
Time‐delay systems are widely used to model real problems. Most of the works on such systems assume prior knowledge of the delay, which is mostly unknown in real applications. This paper aims to fast and robustly estimate unknown delay, parameters, and output derivatives for a class of linear time‐delay systems in noisy environment. First, the classical modulating functions method is combined with the recursive least square algorithm and the Gauss–Newton method to estimate the coefficients and the time‐delay, respectively. Second, the generalized modulating functions method is adopted to provide algebraic integral formulas to estimate the output derivatives using the estimated parameters. Finally, numerical simulations are given to demonstrate the efficiency and robustness of the proposed methods.
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Self-citation
Metadata
- Authors
- Asiri, S., & Liu, D.
- Affiliations
- King Abdulaziz University (SA)
- Université d'Orléans (FR)
- Corresponding author
- Liu, Da‐Yan
- Venue
- Asian Journal of Control
- Publisher
- Wiley
- Published
- 2022-06-10
- Volume
- 25
- Issue
- 2
- Pages
- 746-757
- ISSN
- 1561-8625 (ISSN-L)
- 1934-6093
- OpenAlex
- W4281654354
- Semantic Scholar
- b06f394957c78a7d5188bab73ff2649ecff36e78
- Cited by
- 18
- References
- 33
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 7 · 2023: 2 · 2022: 1
- FWCI
- 1.37
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Asian Journal of Control (publishedVersion)
- HAL (submittedVersion)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
- Physical Sciences › Engineering › Control and Systems Engineering › Stability and Control of Uncertain Systems
- Physical Sciences › Mathematics › Applied Mathematics › Statistical and numerical algorithms
- Keywords
- finite-time estimation, unknown time delay, linear time-delay systems, parameter estimation, recursive least squares, Gauss-Newton method, noisy environments
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