Aerodynamic Moment Model Calibration From Distributed Pressure Arrays
Abstract
In recent years, studies on the role of distributed airflow mechanosensors in bird, bat, and insect flight behaviors have sparked a growing interest in integrating flow sensors, such as pressure or hair sensors, into flight control feedback systems of small unmanned aircraft. It is anticipated that a flight controller based on real-time distributed flow information feedback is more capable of rapidly responding to sudden airflow changes and may exhibit greater stability robustness properties than purely inertial feedback-based flight control laws. However, considering the uncertainty of state-of-the-art microflow sensor technologies, there is an urgent need for model calibration if flow information is to be used to calculate aerodynamic moments and/or forces for controlling aircraft motion. In this paper, a constrained least-squares estimator is developed to calculate the bias of distributed flow information to calibrate an aerodynamic moment model. Simulation and wind-tunnel experiment results demonstrate a significant improvement on the accuracy of the aerodynamic moment calculation after calibration.
Publication Date
1-1-2017
Publication Title
Journal of Aircraft
Volume
54
Issue
2
Number of Pages
716-723
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.2514/1.C033898
Copyright Status
Unknown
Socpus ID
85018488148 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85018488148
STARS Citation
Thompson, Kenneth; Xu, Yunjun; and Dickinson, Benjamin T., "Aerodynamic Moment Model Calibration From Distributed Pressure Arrays" (2017). Scopus Export 2015-2019. 6152.
https://stars.library.ucf.edu/scopus2015/6152