Engineering topics

Klein, V.

Publications and source records attributed to Klein, V..

26 records · Page 2

NASA NTRS1981

Analytical techniques for the analysis of stall/spin flight test data

Analytical techniques for the analysis of stall/spin flight test data are reviewed by discussing (1) certain special flight instrumentation issues, (2) the mathematical modeling techniques, and (3) the analysis of post stall and spinning flight of general aviation airplanes. The angles of attack, sideslip, roll, pitch, and yaw are derived from measurements of angular velocity and linear acceleration. The key to the success of this approach is to simultaneously estimate both the biases in the instrumentation and the initial conditions. Techniques for determining stability derivatives from flight data are applied to angles of attack too high for stabilized flight. This practice greatly expands the range over which aerodynamic characteristics can be determined from flight test. Nonlinear terms in certain aerodynamic functions are shown to be valid by comparing them with the trends of results at different angles of attack. A very old technique of studying spins is extended and applied to some modern light airplanes. Airplanes for which the wing provides the dominant moments during spins, offer the possibility of linking spin characteristics to longitudinal data.

Taylor, L. W., Jr.↗

NASA NTRS1980

Maximum likelihood method for estimating airplane stability and control parameters from flight data in frequency domain

A frequency domain maximum likelihood method is developed for the estimation of airplane stability and control parameters from measured data. The model of an airplane is represented by a discrete-type steady state Kalman filter with time variables replaced by their Fourier series expansions. The likelihood function of innovations is formulated, and by its maximization with respect to unknown parameters the estimation algorithm is obtained. This algorithm is then simplified to the output error estimation method with the data in the form of transformed time histories, frequency response curves, or spectral and cross-spectral densities. The development is followed by a discussion on the equivalence of the cost function in the time and frequency domains, and on advantages and disadvantages of the frequency domain approach. The algorithm developed is applied in four examples to the estimation of longitudinal parameters of a general aviation airplane using computer generated and measured data in turbulent and still air. The cost functions in the time and frequency domains are shown to be equivalent; therefore, both approaches are complementary and not contradictory. Despite some computational advantages of parameter estimation in the frequency domain, this approach is limited to linear equations of motion with constant coefficients.

Klein, V.↗

NASA NTRS1980

Determination of instrumentation errors from measured data using maximum likelihood method

The maximum likelihood method is used for estimation of unknown initial conditions, constant bias and scale factor errors in measured flight data. The model for the system to be identified consists of the airplane six-degree-of-freedom kinematic equations, and the output equations specifying the measured variables. The estimation problem is formulated in a general way and then, for practical use, simplified by ignoring the effect of process noise. The algorithm developed is first applied to computer generated data having different levels of process noise for the demonstration of the robustness of the method. Then the real flight data are analyzed and the results compared with those obtained by the extended Kalman filter algorithm.

Keskar, D. A.↗

NASA NTRS1979

Identification evaluation methods

Methods for airplane parameter estimation, the equation error method, output error method, and two advanced methods are presented and their basic properties described. The advanced methods include the maximum likelihood and extended Kalman filter method. For a better understanding of the estimation techniques a first-order scalar differential equation is used as a model of the system under test. Application of the methods to a general multivariable linear system is briefly outlined. A note on the parameter estimation in the frequency domain is also presented. Numerical examples along with the comparison of results from various methods are given.

Klein, V.↗

NASA NTRS1979

Determination of stability and control parameters of a light airplane from flight data using two estimation methods

Two identification methods, the equation error method and the output error method, are used to estimate stability and control parameter values from flight data for a low-wing, single-engine, general aviation airplane. The estimated parameters from both methods are in very good agreement primarily because of sufficient accuracy of measured data. The estimated static parameters also agree with the results from steady flights. The effect of power different input forms are demonstrated. Examination of all results available gives the best values of estimated parameters and specifies their accuracies.

Klein, V.↗

NASA NTRS1978

Aircraft parameter estimation in frequency domain

The algorithms for the equation error and output error methods, the two basic procedures for the extraction of aircraft parameters from flight data, are formulated in the frequency domain. The output error method includes the maximum likelihood estimation technique. This is further extended to those cases where the measured data is in the form of frequency response curves and the model of an aircraft includes elastic degrees of freedom and unsteady aerodynamics. Then the generalized maximum likelihood method, which can be applied to the identification of an aircraft subjected to external disturbances, is introduced. Next, all estimation methods mentioned are discussed with emphasis on advantages of the frequency domain analysis. The paper concludes with an example using real flight data.

Klein, V.↗

NASA NTRS1977

Compatibility check of measured aircraft responses using kinematic equations and extended Kalman filter

An extended Kalman filter smoother and a fixed point smoother were used for estimation of the state variables in the six degree of freedom kinematic equations relating measured aircraft responses and for estimation of unknown constant bias and scale factor errors in measured data. The computing algorithm includes an analysis of residuals which can improve the filter performance and provide estimates of measurement noise characteristics for some aircraft output variables. The technique developed was demonstrated using simulated and real flight test data. Improved accuracy of measured data was obtained when the data were corrected for estimated bias errors.

Klein, V.↗

NASA NTRS1977

Determination of longitudinal aerodynamic derivatives from steady-state measurement of an aircraft

A method for the estimation of aerodynamic derivatives from steady-state symmetric flight data is developed. The derivatives considered are the longitudinal static stability and control derivatives, damping derivatives due to tail, and the derivatives expressing the speed effect on the lift and pitching moment coefficients. The method is an extension of the well known theory of longitudinal static stability and control, and corresponding flight data interpretation. Measured data is assumed in the form of trim curves and lift vs angle of attack. The expressions for the derivative estimates are in the form of algebraic relationships containing known constants, and directly or indirectly measured quantities.

Klein, V.↗