Hybrid Adaptive Control for Tiltrotor Aircraft Flight Control Law Reconfiguration
Author:
Affiliation:
1. National Key Laboratory of Helicopter Aeromechanics, College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210001, China
2. Hongdu Aviation Industry Group (AVIC), Nanchang 330024, China
Abstract
Funder
Jiangxi Province Key Research and Development Program: Research on Key Technologies of High-Speed VTOL Vehicles
Publisher
MDPI AG
Subject
Aerospace Engineering
Link
https://www.mdpi.com/2226-4310/10/12/1001/pdf
Reference30 articles.
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3. Swinney, C.J., and Woods, J.C. (2021). Unmanned Aerial Vehicle Operating Mode Classification Using Deep Residual Learning Feature Extraction. Aerospace, 8.
4. Wada, D., Araujo-Estrada, S.A., and Windsor, S. (2021). Unmanned Aerial Vehicle Pitch Control under Delay Using Deep Reinforcement Learning with Continuous Action in Wind Tunnel Test. Aerospace, 8.
5. Wang, J., Wu, Y., Liu, M., Yang, M., and Liang, H. (2022). A Real-Time Trajectory Optimization Method for Hypersonic Vehicles Based on a Deep Neural Network. Aerospace, 9.
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