Aerodynamic parameters estimated from flight and wind tunnel data
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Klein, V.↗
Engineering topics
Klein, V.
Publications and source records attributed to Klein, V..
Estimation of aerodynamic parameters from flight data of a high incidence research model
A procedure for the determination of an aerodynamic model structure and aerodynamic parameters is applied to flight data from a high-incidence research model (HIRM) within an angle of attack range of 18 to 40 degrees. The HIRM is a three-surface unpowered model with a swept wing, an all-moving canard and stabilator, and a vertical tail with rudder. The motion of the HIRM was excited first by its release from the helicopter and then by the activation of control surfaces. This paper briefly describes the model, flight and wind tunnel data available, equations of motion and techniques for data analysis. The results presented contain an example of a measured data compatibility and the variation of some important stability derivatives with the angle of attack and canard setting. The derivatives were obtained from various maneuvers and subsets of joined data from several maneuvers by using a stepwise-regression technique. These derivatives agreed, in general, with the results of wind-tunnel measurements. The resulting lateral aerodynamic model equations could predict the motion of the HIRM reasonably well.
Klein, V.↗
On the identification of a highly augmented airplane
The results of applying linear least squares and maximum likelihood estimation procedures to flight data from the AFTI/F-16 airplane are presented. Data from two flight control system modes are analyzed. It is shown that though a simple aerodynamic model structure is adequate for the simple mode, a more complicated model is necessary to adequately describe the highly augmented mode. The effect of augmentation of roll control is shown to be visible in the control parameters.
Batterson, J. G.↗
Estimation of transport airplane aerodynamics using multiple stepwise regression
This paper presents an application of multiple stepwise regression to the flight test data of a typical transport airplane. The flight test data was carefully preprocessed to eliminate aliasing, time skews and high frequency noise. The data consisted both of basic certification maneuvers, such as wind-up-turns and maneuvers suitable for parameter estimation, such as responses to elevator pulses and doublets. It is shown that the results of multiple stepwise regression techniques compare favorably with the results obtained from maximum likelihood estimation. Finally, it is concluded that multiple stepwise regression could be a fast economical way to estimate transport airplane aerodynamics.
Keskar, D. A.↗
Parameter identification applied to the oscillatory motion of an airplane near stall
Previously cited in issue 19, p. 2804, Accession no. A83-41905
Batterson, J. G.↗
Applications of model structure determination to flight test data
Several statistical and information criteria need to be considered when selecting an adequate model. Incorrect stability and control derivates result from inadequate aerodynamic model structure. Stepwise regression is used to determine the structure for an adequate model. Flight data which covers a nonlinear aerodynamic model range may be analyzed as a single data set or partitioned into several distinct sets. Stepwise regression for model structure detemination and parameter estimation was successfully applied to three aircraft types (single engine general aviation, unaugmented modern jet fighter, jet transport).
Batterson, J. G.↗
Maximum likelihood algorithm using an efficient scheme for computing sensitivities and parameter confidence intervals
Improved techniques for estimating airplane stability and control derivatives and their standard errors are presented. A maximum likelihood estimation algorithm is developed which relies on an optimization scheme referred to as a modified Newton-Raphson scheme with estimated sensitivities (MNRES). MNRES determines sensitivities by using slope information from local surface approximations of each output variable in parameter space. The fitted surface allows sensitivity information to be updated at each iteration with a significant reduction in computational effort compared to integrating the analytically-determined sensitivity equations or using a finite difference scheme. An aircraft estimation problem is solved using real flight data to compare MNRES with the commonly used modified Newton-Raphson technique; MNRES is found to be faster and more generally applicable. Parameter standard errors are determined using a random search technique. The confidence intervals obtained are compared with Cramer-Rao lower bounds at the same confidence level. It is observed that the nonlinearity of the cost function is an important factor in the relationship between Cramer-Rao bounds and the error bounds determined by the search technique.
Murphy, P. C.↗
A preliminary analysis of flight data from the AFTI/F-16 airplane
Flight test data from the AFTI/F-16 airplane are analyzed. Two flight control system modes (Independent Backup Unit and Standard Normal Mode) are considered. Estimated stability and control derivatives are compared with values from the wind tunnel and F-16A flight tests. Modeling difficulties are shown to arise due to the near-neutral static stability of the airplane and the number of coordinated control surface movements commanded in the Standard Normal Mode.
Batterson, J. G.↗
Estimated low-speed aerodynamic parameters of an advanced fighter from flight and wind tunnel data
A procedure for determination of aerodynamic model structure and estimation of aerodynamic parameters is applied to data from a modern fighter operating within an angle of attack range of 5 to 60 deg. The paper briefly describes the airplane, flight and wind tunnel data available, postulated models for airplane aerodynamic coefficients and flight data analysis. The results presented contain only a small number of selected longitudinal and lateral parameters. These parameters were obtained from various maneuvers and subsets of joined data from several flights. The estimated parameters are in good agreement with the wind tunnel measurements. The resulting aerodynamic model equations seem to be satisfactory for the prediction of airplane motion.
Klein, V.↗
A Review of System Identification Methods Applied to Aircraft
Airplane identification, equation error method, maximum likelihood method, parameter estimation in frequency domain, extended Kalman filter, aircraft equations of motion, aerodynamic model equations, criteria for the selection of a parsimonious model, and online aircraft identification are addressed.
Klein, V.↗
Determination of aerodynamic parameters of a fighter airplane from flight data at high angles of attack
A procedure for the estimation of airplane model structure and parameters is applied to data from a modern fighter airplane operating within an angle of attack range of 5 to 60 deg. The paper briefly describes the airplane, flight and wind tunnel data available, and the estimation method. The results presented contain basic longitudinal characteristics of the airplane and the estimates of aerodynamic parameters in the yawing-moment equations. These estimates are obtained from small and large amplitude maneuvers. Because the latter set of data was not suitable for airplane identification, some of the large amplitude maneuvers were joined together and then partitioned into subsets according to the values of angle of attack. Each subset was then analyzed as a separate data set. Most of the estimated parameters and functions are in good agreement with the wind tunnel measurements. The estimated lateral parameters in the model equations also demonstrate good prediction capabilities.
Klein, V.↗
An application of parameter identification to the oscillatory motion of an airplane at high C(L)
This paper presents an application of a stepwise regression incorporating polynomial splines to oscillatory flight data from a light research airplane operating at near stall angles of attack. It is shown that data from several experiments can be combined into a large data set for analysis and that hysteresis phenomena can be observed in this large data set. Finally, it is postulated from the analysis of the flight data and theoretical calculations that the observed oscillatory motion is the result of a combination of wing stall and wing wake position at the tail.
Batterson, J. G.↗
Airplane model structure determination from flight data
Previously cited in issue 21, p. 3626, Accession no. A81-44562
Klein, V.↗
Determination of airplane model structure from flight data using splines and stepwise regression
A procedure for the determination of airplane model structure from flight data is presented. The model is based on a polynomial spline representation of the aerodynamic coefficients, and the procedure is implemented by use of a stepwise regression. First, a form of the aerodynamic force and moment coefficients amenable to the utilization of splines is developed. Next, expressions for the splines in one and two variables are introduced. Then the steps in the determination of an aerodynamic model structure and the estimation of parameters are discussed briefly. The focus is on the application to flight data of the techniques developed.
Klein, V.↗
On the determination of airplane model structure form flight data
A procedure based on a modified stepwise regression and several selection criteria is presented for the determination of airplane model structure from flight data. The aerodynamic force and moment coefficients in an airplane model are expresed either as polynomials in output and input variables or as a combination of splines. The procedure is demonstrated in three examples by attempting to determine a local, extended and global model. Some of the resulting models are verified by using the maximum likelihood estimation or by examining model prediction capabilities.
Klein, V.↗
Determination of airplane aerodynamic parameters from flight data at high angles of attack
The problem of determining airplane aerodynamic model equations and estimating the associated parameters from flight data taken at high angles of attack is addressed. Two representations of the aerodynamic function based on the polynomial and spline representations are given. Then the technique of building an adequate model using a stepwise regression is presented with examples demonstrating the construction of the model and various approaches to model verification.
Klein, V.↗
Determination of airplane model structure from flight data by using modified stepwise regression
The linear and stepwise regressions are briefly introduced, then the problem of determining airplane model structure is addressed. The MSR was constructed to force a linear model for the aerodynamic coefficient first, then add significant nonlinear terms and delete nonsignificant terms from the model. In addition to the statistical criteria in the stepwise regression, the prediction sum of squares (PRESS) criterion and the analysis of residuals were examined for the selection of an adequate model. The procedure is used in examples with simulated and real flight data. It is shown that the MSR performs better than the ordinary stepwise regression and that the technique can also be applied to the large amplitude maneuvers.
Klein, V.↗
Determination of model structure and parameters of an airplane from pre- and post-stall flight data
A procedure for airplane model structure determination from flight data based on modified stepwise regression (MSR), several decision criteria and postulated aerodynamic model equations is presented. The MSR is constructed to force a linear model for the aerodynamic coefficient first, then select significant nonlinear terms and reject nonsignificant terms from the model. In addition to the statistical criteria in the stepwise regression, the prediction sum of squares (PRESS) criterion and analysis of residuals are examined for the selection of an adequate model. The procedure is used in examples with simulated and real flight data. It is shown that the MSR performs better than the ordinary stepwise regression and that the technique can be also applied to the large amplitude maneuvers.
Klein, V.↗