Selma Benattia
Papers
1
Total Citations
5
H-Index
1
About
Selma Benattia is a researcher focused on the real-time identification and control of mechanical systems, with a particular emphasis on vibration analysis and parameter estimation. Her work addresses the challenge of extracting accurate dynamic information from noisy, biased sensor signals—a critical problem in robotics, structural health monitoring, and precision machinery. In her most-cited paper, "A Fast Online Estimator of the Main Vibration Mode of Mechanisms from a Biased Slightly Damped Signal" (2022), Benattia introduces two novel algorithms rooted in algebraic identification theory. These methods robustly estimate the dominant vibration mode parameters (such as natural frequency and damping ratio) of slightly damped elastic systems, even when sensor offset corrupts the signal. By enabling fast, online computation without requiring prior knowledge of the bias, her approach significantly improves the practicality of vibration monitoring in real-world applications. Though early in her career, her work has already garnered attention for its theoretical rigor and practical utility, laying a strong foundation for future advances in adaptive control and system identification.
Research Focus
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Top Papers
- 1