JOURNAL ARTICLE
Hardware-in-the-loop simulation test platform for UAV flight control system.
Published In: International Journal of Modeling, Simulation & Scientific Computing, 2024, v. 15, n. 2. P. 1 1 of 3
Database: Applied Science & Technology Source Ultimate 2 of 3
Authored By: Lu, Wenjun 3 of 3
Abstract
The flight control system is the integrated command center and core component of the UAV system. Aiming at the problems of poor accuracy and low efficiency in the field measurement of flight control system parameters, combined with the configuration of the flight attitude sensor-vertical gyroscope, hardware-in-the-loop simulation technology, and integrated automatic test methods are adopted. The hardware-in-the-loop simulation test platform for the UAV flight control system composed of a low-cost, high-precision miniaturized UAV attitude calibration platform and a control piston deflection angle test device is designed. The main controller replaces the ground master control station of the UAV and directly sends remote control commands to the aircraft. By changing the attitude of the aircraft, and measuring the voltage of the control signal, the feedback signal, and the rudder angle, the comprehensive performance test of the parameters of the flight control system is realized. The performance test of the platform shows that the platform can meet the test requirements of angular position, system voltage, and control piston deflection angle. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Modeling, Simulation & Scientific Computing. 2024/04, Vol. 15, Issue 2, p1
- Document Type:Article
- Subject Area:Engineering
- Publication Date:2024
- ISSN:17939623
- DOI:10.1142/S1793962324410186
- Accession Number:177091173
- Copyright Statement:Copyright of International Journal of Modeling, Simulation & Scientific Computing is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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