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Various practical aspects of the equation-error approach to aircraft parameter estimation were examined. The analysis was based on simulated flight data from an F-16 nonlinear simulation, with realistic noise sequences added to the computed aircraft responses. This approach exposes issues related to the parameter estimation techniques and results, because the true parameter values are known for simulation data. The issues studied include differentiating noisy time series, maximum likelihood parameter estimation, biases in equation-error parameter estimates, accurate computation of estimated parameter error bounds, comparisons of equation-error parameter estimates with output-error parameter estimates, analyzing data from multiple maneuvers, data collinearity, and frequency-domain methods.

A global nonlinear parametric modeling technique is described and demonstrated. The technique uses multivariate orthogonal modeling functions generated from the data to determine nonlinear niodel structure, then expands each retained modeling function into an ordinary multivariate polynomial. The final model form is a finite multivariate power series expansion for the dependent variable in terms of the independent variables. Partial derivatives of the identified models can be used to assemble globally valid linear parameter varying models. The technique is demonstrated by identifying global nonlinear parametric models for nondimensional aerodynamic force and moment coefficients from a subsonic wind tunnel database for the F-16 fighter aircraft. ]Results show less than 10% difference between wind tunnel aerodynamic data and the nonlinear parameterized model for a simulated doublet maneuver at moderate angle of attack. Analysis indicated that the global nonlinear parametric models adequately captured the multivariate nonlinear aerodynamic functional dependence. X cgref NOMENCLATURE wing reference chord, ft win;: span, ft aerodynamic force coefficients aerodynamic moment coefficients body axis angular rates, rad/sec predicted squared e m r airspeed, ft/sec angle of attack, rad sideslip angle, rad elevator, aileron, rudder deflections, rad longitudinal c.g. position reference longitudinal c.g. position = 0.35Recently, a method has been developed which identifies

A method for real-time estimation of parameters in a linear dynamic state space model was developed and studied. The application is aircraft dynamic model parameter estimation from measured data in flight for indirect adaptive or reconfigurable control. Equation error in the frequency domain was used with a recursive Fourier transform for the real-time data analysis. Linear and nonlinear simulation examples and flight test data from the F-18 High Alpha Research Vehicle (HARV) were used to demonstrate that the technique produces accurate model parameter estimates with appropriate error bounds. Parameter estimates converged in less than 1 cycle of the dominant dynamic mode natural frequencies, using control surface inputs measured in flight during ordinary piloted maneuvers. The real-time parameter estimation method has low computational requirements, and could be implemented aboard an aircraft in real time. Nomenclature A, B,C, Dsystem matrices E ; @

A maneuver design method that is particularly well-suited for determining the stability and control characteristics of hypersonic vehicles is described in detail. Analytical properties of the maneuver design are explained. The importance of these analytical properties for maximizing information content in flight data is discussed, along with practical implementation issues. Results from flight tests of the X-43A hypersonic research vehicle (also called Hyper-X) are used to demonstrate the excellent modeling results obtained using this maneuver design approach. A detailed design procedure for generating the maneuvers is given to allow application to other flight test programs.