Estimation of the aerodynamic parameters for a flight vehicle from flight test

1995 ◽  
Author(s):  
Chang-Joon Song ◽  
In-Soo Jeon ◽  
Sung-Mhan Lee ◽  
Sang-Joo Kwon
Keyword(s):  
Flight Test ◽  
Flight Vehicle ◽  
Aerodynamic Parameters

scholarly journals Method for designing multi-input system identification signals using a compact time-frequency representation

2021 ◽  
Author(s):  
Mathias Stefan Roeser ◽  
Nicolas Fezans
Keyword(s):  
System Identification ◽  
Design Method ◽  
Flight Test ◽  
Compact Representation ◽  
Time Frequency ◽  
Stability And Control ◽  
Frequency Representation ◽  
Aerodynamic Parameters ◽  
Definition Of ◽  
And Control

AbstractA flight test campaign for system identification is a costly and time-consuming task. Models derived from wind tunnel experiments and CFD calculations must be validated and/or updated with flight data to match the real aircraft stability and control characteristics. Classical maneuvers for system identification are mostly one-surface-at-a-time inputs and need to be performed several times at each flight condition. Various methods for defining very rich multi-axis maneuvers, for instance based on multisine/sum of sines signals, already exist. A new design method based on the wavelet transform allowing the definition of multi-axis inputs in the time-frequency domain has been developed. The compact representation chosen allows the user to define fairly complex maneuvers with very few parameters. This method is demonstrated using simulated flight test data from a high-quality Airbus A320 dynamic model. System identification is then performed with this data, and the results show that aerodynamic parameters can still be accurately estimated from these fairly simple multi-axis maneuvers.

scholarly journals The Effects of Icing on Aircraft Longitudinal Aerodynamic Characteristics

Mathematics ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 1171
Author(s):  
Yihua Cao ◽  
Wenyuan Tan ◽  
Yuan Su ◽  
Zhongda Xu ◽  
Guo Zhong
Keyword(s):  
Prediction Method ◽  
Flight Test ◽  
Aerodynamic Characteristics ◽  
Identification System ◽  
Narrow Strip ◽  
Aerodynamic Derivatives ◽  
Strip Theory ◽  
Aerodynamic Parameters ◽  
Flight Dynamics Model ◽  
Derivatives Of

To study the effects of ice accretion on the longitudinal aerodynamic characteristics of an aircraft, a two-part method for predicting longitudinal aerodynamic derivatives of iced aircraft is proposed. For the aircraft with a flight test, a parameter identification system based on maximum likelihood criterion and a longitudinal nonlinear flight dynamics model is established. For the aircraft without a flight test, an engineering prediction method of aerodynamic derivatives based on an individual component CFD calculation and narrow strip theory is established. According to the flight test data of DHC-6 Twin Otter aircraft from NASA, the longitudinal aerodynamic parameters of both clean and artificially iced aircraft are obtained. Additionally, the longitudinal aerodynamic derivatives of the iced aircraft are calculated. Then, the correctness of the prediction method is verified by comparing the calculated results with the identification results. The comparison of these results shows that the prediction method is correct and accurate, and it can be used to calculate the effects of icing on the aircraft longitudinal aerodynamic parameters.

A comparative study of parameter estimation techniques applied to jettisoned external stores

2014 ◽  
Vol 118 (1204) ◽  
pp. 601-624
Author(s):  
G. Guglieri ◽  
P. Marguerettaz ◽  
G. Simioni
Keyword(s):  
Initial Conditions ◽  
Fitness Function ◽  
Computational Cost ◽  
Flight Test ◽  
Identification Problem ◽  
Least Square ◽  
Computational Time ◽  
Covariance Matrix Adaptation ◽  
Parameter Identification Problem ◽  
Aerodynamic Parameters

AbstractThe present work evaluates the performance of different optimisation techniques on a parameter identification problem of aeronautical interest. In particular, the focus is on the classical Least Square (LS) and Maximum Likelihood (ML) methods and on the CMAES (Covariance Matrix Adaptation Evolution Strategy), DE (Differential Evolution), GA (Genetic Algorithm) and PSO (Particle Swarm Optimisation) Meta-Heuristic methods. The test problem is the reconstruction from flight test data of the aerodynamic parameters of an external store jettisoned from a helicopter. Different initial conditions and the presence of measurement noise are considered. This case is representative of a class of problems of difficult solution because of nonlinearity, ill-conditioning, multidimensionality, non separability, and fitness function dispersion. Only reference algorithm implementations found in literature are used. The performance of each algorithm are defined in terms of fitness function value, sum of absolute errors of the estimated coefficients, computational time and number of function evaluations. The results show the efficiency of CMAES in finding the best estimates with the least computational cost. Moreover, tests reveal that traditional methods depend heavily on problem characteristics and loose accuracy at the increase of the number of unknowns.

scholarly journals ESTIMATION OF THE LATERAL AERODYNAMIC COEFFICIENTS FOR SKYWALKER X8 FLYING WING FROM REAL FLIGHT-TEST DATA

2018 ◽  
Vol 58 (2) ◽  
pp. 77
Author(s):  
Rahman Mohammadi Farhadi ◽  
Vyacheslav Kortunov ◽  
Andrii Molchanov ◽  
Tatiana Solianyk
Keyword(s):  
Test Data ◽  
Flight Test ◽  
Least Square ◽  
Stability And Control ◽  
Information Parameter ◽  
Control Derivatives ◽  
Aerial Vehicle ◽  
Aerodynamic Parameters ◽  
Priori Information ◽  
And Control

Stability and control derivatives of Skywalker X8 flying wing from flight-test data are estimated by using the combination of the output error and least square methods in the presence of the wind. Data is collected from closed loop flight tests with a proportional-integral-derivative (PID) controller that caused data co-linearity problems for the identification of the unmanned aerial vehicle (UAV) dynamic system. The data co-linearity problem is solved with a biased estimation via priori information, parameter fixing and constrained optimization, which uses analytical values of aerodynamic parameters, the level of the identifiability and sensitivity of the measurement vector to the parameters. Estimated aerodynamic parameters are compared with the theoretically calculated coefficients of the UAV, moreover, the dynamic model is validated with additional flight-test data and small covariances of the estimated parameters.

Parameter Identification of Tailplane Iced Aircraft Based on Maximum Likelihood Method

2012 ◽  
Vol 192 ◽  
pp. 57-62 ◽  
Author(s):  
Zhong Da Xu ◽  
Yi Hua Cao ◽  
Ming Zhao
Keyword(s):  
Maximum Likelihood ◽  
Parameter Identification ◽  
Maximum Likelihood Method ◽  
Flight Test ◽  
Likelihood Method ◽  
Identification System ◽  
Flight Performance ◽  
Aerodynamic Parameters ◽  
Flight Dynamics Model ◽  
Ice Shapes

Based on the maximum likelihood method, this paper analyzed the influence of tailplane icing on aerodynamic parameters by parameter identification. A nonlinear longitudinal flight dynamics model for aircraft was built, and an identification system was constructed using maximum likelihood method. According to the flight test data of DHC-6 aircraft, the aerodynamic parameters of clean aircraft and two different cases of iced aircraft with particular ice shapes on the tailplane were identified. Eventually, the results of the identification show that the tailplane icing has several adverse effects on the aircraft flight characteristics, including flight performance, elevator effectiveness, stability and safety.

Helicopter Aerodynamic Parameter Identification via Flight Dynamics

2013 ◽  
Vol 327 ◽  
pp. 246-249
Author(s):  
Xue Mei Yu ◽  
An Ping Zhao ◽  
Xue Li
Keyword(s):  
Parameter Identification ◽  
Least Squares ◽  
Test Data ◽  
Least Squares Method ◽  
Flight Dynamics ◽  
Flight Test ◽  
Mathematic Model ◽  
Feasibility Analysis ◽  
Aerodynamic Parameter ◽  
Aerodynamic Parameters

A method which can process flight test data by integrating parameter identification and non-dimensional flight dynamic model was proposed to acquire the effective aerodynamic parameters of a helicopter. First of all, a non-dimensional mathematic model considering flight dynamics was deduced for a helicopter in state of level flight, and some important parameters including aerodynamic and correctional were developed. Next, taking helicopter Z-9× for example, the least squares method was adopted to identify these parameters based actual flight test data. Lastly, the identification method was proved valid through feasibility analysis. Results show that this method is a good way to acquire aerodynamic parameters and can shorten flight test periods as well.

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