Study on the identification of bridge aerodynamic derivatives with Poly Reference Complex Exponent (PRCE) method

2010 ◽  
Author(s):  
Yang Zhuanyun
Keyword(s):  
Complex Exponent ◽  
Aerodynamic Derivatives

Aeroelastic Problems in connection with High-Speed Flight

1956 ◽  
Vol 60 (547) ◽  
pp. 459-475 ◽  
Author(s):  
E. G. Broadbent
Keyword(s):  
Mach Number ◽  
High Speed ◽  
The Other ◽  
Control Surface ◽  
The Past ◽  
Other Hand ◽  
Aerodynamic Derivatives ◽  
Mach Numbers ◽  
The One

SummaryA review is given of developments in the field of aeroelasticity during the past ten years. The effect of steadily increasing Mach number has been two-fold: on the one hand the aerodynamic derivatives have changed, and in some cases brought new problems, and on the other hand the design for higher Mach numbers has led to thinner aerofoils and more slender fuselages for which the required stiffness is more difficult to provide. Both these aspects are discussed, and various methods of attack on the problems are considered. The relative merits of stiffness, damping and massbalance for the prevention of control surface flutter are discussed. A brief mention is made of the recent problems of damage from jet efflux and of the possible aeroelastic effects of kinetic heating.

Aerodynamic coefficients modeling using Levenberg–Marquardt algorithm and network

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhigang Wang ◽  
Aijun Li ◽  
Lihao Wang ◽  
Xiangchen Zhou ◽  
Boning Wu
Keyword(s):  
Neural Network ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Aerodynamic Parameter ◽  
Content Type ◽  
Flight Data ◽  
Output Error ◽  
Aerodynamic Derivatives ◽  
Levenberg Marquardt ◽  
Error Method

Purpose The purpose of this paper is to propose a new aerodynamic parameter estimation methodology based on neural network and output error method, while the output error method is improved based on particle swarm algorithm. Design/methodology/approach Firstly, the algorithm approximates the dynamic characteristics of aircraft based on feedforward neural network. Neural network is trained by extreme learning machine, and the trained network can predict the aircraft response at (k + 1)th instant given the measured flight data at kth instant. Secondly, particle swarm optimization is used to enhance the convergence of Levenberg–Marquardt (LM) algorithm, and the improved LM method is used to substitute for the Gauss Newton algorithm in output error method. Finally, the trained neural network is combined with the improved output error method to estimate aerodynamic derivatives. Findings Neither depending on the initial guess of the parameters to be estimated nor requiring numerical integration of the aircraft motion equation, the proposed algorithm can be used for unstable aircraft and is successfully applied to extract aerodynamic derivatives from both simulated and real flight data. Research limitations/implications The proposed method requires iterative calculation and can only identify parameters offline. Practical implications The proposed method is successfully applied to estimate aircraft aerodynamic parameters and can also be used as a new algorithm for other optimization problems. Originality/value In this study, the output error method is improved to reduce the dependence on the initial value of parameters and expand its application scope. It is applied in aircraft aerodynamic parameter identification together with neural network.

The investigation on flight quality of tilt-rotor aircraft

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ke Lu ◽  
Shanyong Zhao ◽  
YUjie Ma ◽  
Shangjing Wu ◽  
Cheng da Su
Keyword(s):  
Tracking Control ◽  
Control Method ◽  
Quantitative Relationship ◽  
Explicit Model ◽  
Content Type ◽  
Tilt Rotor ◽  
Motion Modes ◽  
Aerodynamic Derivatives ◽  
Quality Specifications

Purpose This paper aims to present an investigation on flight quality analysis and design of tilt-rotor aircraft combined with corresponding flight quality specifications. Design/methodology/approach From the perspective of modal characteristics of tilt-rotor aircraft, it focuses on the analysis of the change rules of the longitudinal short-term motion mode, lateral roll convergence mode, spiral mode and Dutch roll mode. Then, the flight quality design research is carried out using the explicit model tracking control method. The quantitative relationship between flight quality requirements and explicit model is established. Accordingly, the closed-loop flight quality of XV-15 tilt-rotor aircraft is evaluated. Findings The stability of spiral mode is the result of the interaction of various aerodynamic derivatives and spiral instability occurs in helicopter mode. The other motion modes are stable in full flight mode and meet the requirements of level 1 specified in ADS-33E-PRF and MIL-F-8785C flight quality specifications. There is a quantitative relationship between flight quality requirements and explicit model, and the flight quality of tilt-rotor aircraft is improved through the explicit model tracking control method. Practical implications The presented analysis results showed the influence of motion modes and flight quality and the effectiveness of explicit model tracking control method in flight quality improvement, which could be considered as new information for further flight quality design of tilt-rotor aircraft. Originality/value The originality of the paper lies in the proposed design and analysis method of the flight quality of tilt-rotor aircraft from the direction of the influence of its aerodynamic derivatives and motion modes.

scholarly journals Identification of Fixed-Wing Micro Aerial Vehicle Aerodynamic Derivatives from Dynamic Water Tunnel Tests

Aerospace ◽  
2020 ◽  
Vol 7 (8) ◽  
pp. 116
Author(s):  
Krzysztof Sibilski ◽  
Mirosław Nowakowski ◽  
Dariusz Rykaczewski ◽  
Paweł Szczepaniak ◽  
Andrzej Żyluk ◽  
...  
Keyword(s):  
Unsteady Aerodynamics ◽  
Linear Functions ◽  
Water Tunnel ◽  
Micro Aerial Vehicle ◽  
Indicial Function ◽  
Reduced Frequency ◽  
Aerodynamic Derivatives ◽  
Aerial Vehicle ◽  
Institute Of Technology ◽  
Derivatives Of

A micro air vehicle (MAV) is a class of miniature unmanned aerial vehicles that has a size restriction and may be autonomous. Fixed-wing MAVs are very attractive for outdoor surveillance missions since they generally offer better payload and endurance capabilities than rotorcraft or flapping-wing vehicles of equal size. This research paper describes the methodology applying indicial function theory and artificial neural networks for identification of aerodynamic derivatives for fixed-wing MAV. The formulation herein proposed extends well- known aerodynamic theories, which are limited to thin aerofoils in incompressible flow, to strake wing planforms. Using results from dynamic water tunnel tests and indicial functions approach allowed to identify MAV aerodynamic derivatives. The experiments were conducted in a water tunnel in the course of dynamic tests of periodic oscillatory motion. The tests program range was set at high angles of attack and a wide scope of reduced frequencies of angular movements. Due to a built-in propeller, the model’s structure test program was repeated for a turned-on propelled drive system. As a result of these studies, unsteady aerodynamics characteristics and aerodynamic derivatives of the micro-aircraft were identified as functions of state parameters. At the Warsaw University of Technology and the Air Force Institute of Technology, a “Bee” fixed wings micro aerial vehicle with an innovative strake-wing outline and a propeller placed in the wing gap was worked. This article is devoted to the problems of identification of aerodynamic derivatives of this micro-aircraft. The result of this research was the identification of the aerodynamic derivatives of the fixed wing MAV “Bee” as non-linear functions of the angle of attack, and reduced frequency. The identification was carried out using the indicial function approach.

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