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Flapping Soft Fin Deformation Modeling using Planar Laser-Induced Fluorescence Imaging

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Optimal input signal design for closed loop aircraft flutter model analysis.

Wang Jianhong¹

¹School of Electronic Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou, 341000, Jiangxi, China. wangjianhong@nuaa.edu.cn.

Scientific Reports

|November 18, 2025

Summary

This summary is machine-generated.

This study optimizes input signals for closed-loop aircraft flutter models, improving estimation accuracy despite system noise. The research introduces a robust method for precise identification in practical flight conditions.

Keywords:

Aircraft flutter model Closed loop Composite Lyapunov analysis Nonparametric estimate Optimal input signal

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Area of Science:

Aerospace Engineering
Control Systems
Signal Processing

Background:

Accurate aircraft flutter models are crucial for flight safety and performance.
Previous research focused on open-loop systems, limiting practical applicability.
Closed-loop systems present challenges due to inherent noise and feedback dynamics.

Purpose of the Study:

To extend aircraft flutter model analysis to a more practical closed-loop scenario.
To determine optimal input signals for unbiased nonparametric flutter model estimation.
To enhance accurate system identification in the presence of input-output noises.

Main Methods:

Developed a closed-loop aircraft flutter model analysis.
Derived an explicit improved form for optimal input signal dependence on nonparametric estimates.
Utilized composite Lyapunov analysis for robustness against two distinct noises.

Main Results:

Achieved unbiased nonparametric flutter model identification using closed-loop data.
Demonstrated the explicit dependence of optimal input signals on nonparametric estimates.
Established robustness of the estimation method against system noise.

Conclusions:

The proposed method offers improved accurate identification for closed-loop aircraft flutter models.
The approach effectively handles simultaneous input-output noises, suiting practical experiments.
This work advances techniques for robust system identification in dynamic aerospace applications.