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Data‐driven approach for estimating longitudinal aerodynamic parameters using neural artificial bee colony fusion algorithm
Aerodynamic parameter estimation involves modeling both force and moment coefficients
along with the computation of stability and control derivatives from recorded flight data …
along with the computation of stability and control derivatives from recorded flight data …
Aerodynamic characterisation of delta wing unmanned aerial vehicle using non-gradient-based estimator
Aerodynamic characterisation from flight testing is an integral subroutine for evaluating a
new flight vehicle's aerodynamic performance, stability and controllability. The estimation of …
new flight vehicle's aerodynamic performance, stability and controllability. The estimation of …
Machine Learning Opportunities in Flight Test: Preflight Checks
JR Walker, D Claudio - SN Computer Science, 2024 - Springer
Flight test for aircraft certification is a fundamental method to ensure safe aircraft and air
travel worldwide. Flight test data is collected through a limited number of discrete subspace …
travel worldwide. Flight test data is collected through a limited number of discrete subspace …
Recurrent neural networks for aerodynamic parameter estimation with Lyapunov stability analysis
Aircraft parameter estimation is crucial for designing accurate and reliable flight dynamic
models, essential for integration into flight simulators and develo** effective control laws …
models, essential for integration into flight simulators and develo** effective control laws …
System identification of cropped delta UAVs from flight test methods using particle Swarm-Optimisation-based estimation
In the era of Unmanned Aerial Systems (UAS), an onboard autopilot occupies a prominent
place and is inevitable for many of their modern applications. The efficacy of autopilot …
place and is inevitable for many of their modern applications. The efficacy of autopilot …
Aerodynamic Parameter Estimation for Near-Stall Maneuver Using Neural Networks and Artificial Bee Colony Algorithm
Accurate numerical values of aerodynamic parameters are important in aircraft design. The
knowledge of stability and control aerodynamic parameters is essential to postulate high …
knowledge of stability and control aerodynamic parameters is essential to postulate high …
Physics-Informed Transfer Learning-Based Aerodynamic Parameter Identification of Morphing Aircraft
D Qu, Q Wang, H Liu - Journal of Guidance, Control, and Dynamics, 2025 - arc.aiaa.org
This paper presents an aerodynamic parameter identification method for morphing aircraft
through physics-informed transfer learning. The basic configuration of the morphing aircraft …
through physics-informed transfer learning. The basic configuration of the morphing aircraft …
[PDF][PDF] Sensor Based System Identification in Real Time for Noise Covariance Deficient Models.
System identification methods have extensive application in the aerospace industry's
experimental stability and control studies. Accurate aerodynamic modeling and system …
experimental stability and control studies. Accurate aerodynamic modeling and system …
Review on neural network identification for maneuvering uavs
Y Zheng, H **e - 2018 International Conference on Sensing …, 2018 - ieeexplore.ieee.org
Unmanned Aerial Vehicles (UAV) need high mobility in performing military tasks. In this
paper, we summarized the UAVs identification methods based on neural network, which …
paper, we summarized the UAVs identification methods based on neural network, which …
Assessment of Drag Prediction Techniques for a Flying Vehicle Based on Radar-Tracked Data
As far as the aerodynamic characterization of a flying vehicle is concerned, flight testing is
probably the most accurate approach as it perfectly resembles the real flight environment …
probably the most accurate approach as it perfectly resembles the real flight environment …