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  • 1
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    Identification of M2/F3 stability and control derivatives from flight data containing gust effects (1974)
    In:  Other Sources
    Details
    Publication Date: 2011-08-16
    Description: The application of the maximum likelihood identification technique to M2/F3 lifting body flight data containing wind gust effects is discussed. With the objective of this effort being the identification of the stability and control derivatives, it is shown first that the output error technique (or modified Newton-Raphson) fails to fit the recorded data accurately. The means of applying the maximum likelihood technique to this problem are then discussed and the results given which indicate an accurate fit to the data. The question of derivative signs opposite to the wind tunnel values is then addressed and the results of three techniques for dealing with this problem are presented. These techniques are a priori weighting, fixing parameter values, and rank deficient inverses.
    Keywords: AIRCRAFT
    Type: NASA. Flight Res. Center Parameter Estimation Tech. and Appl. in Aircraft Flight Testing; p 115-124
    Format: text
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    NASA TECHNICAL REPORTS
  • 2
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    Maximum likelihood identification of aircraft stability and control derivatives (1974)
    In:  Other Sources
    Details
    Publication Date: 2019-06-27
    Description: Application of a generalized identification method to flight test data analysis. The method is based on the maximum likelihood (ML) criterion and includes output error and equation error methods as special cases. Both the linear and nonlinear models with and without process noise are considered. The flight test data from lateral maneuvers of HL-10 and M2/F3 lifting bodies are processed to determine the lateral stability and control derivatives, instrumentation accuracies, and biases. A comparison is made between the results of the output error method and the ML method for M2/F3 data containing gusts. It is shown that better fits to time histories are obtained by using the ML method. The nonlinear model considered corresponds to the longitudinal equations of the X-22 VTOL aircraft. The data are obtained from a computer simulation and contain both process and measurement noise. The applicability of the ML method to nonlinear models with both process and measurement noise is demonstrated.
    Keywords: AIRCRAFT
    Type: Journal of Aircraft; 11; Feb. 197
    Format: text
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  • 3
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    A unified approach to aircraft parameter identification (1974)
    In:  Other Sources
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    Publication Date: 2019-06-27
    Description: The most accurate identification results are obtained when all three elements of the identification process - the identification algorithm, the control input, and the instrumentation system - are considered in a unified approach. This type of approach for the design of optimal control inputs and for determining the effect of the instrumentation system, in each case with respect to the identification process is discussed. Design of control inputs which optimize the sensitivity of the system output to the unknown parameters is given. Results using these inputs in an extensive simulation of the identification process indicate they perform measurably better than doublet type inputs. A technique is then presented for specifying an optimal instrumentation system or for determining the effect, the instrumentation system has on the accuracy of the parameter estimates.
    Keywords: AERODYNAMICS
    Type: NASA. Flight Res. Center Parameter Estimation Tech. and Appl. in Aircraft Flight Testing; p 243-259
    Format: text
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  • 4
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    A generalized method for the identification of aircraft stability and control derivatives from flight test data. (1972)
    In:  Other Sources
    Details
    Publication Date: 2019-07-13
    Description: This paper discusses the application of a generalized identification method for flight test data analysis. The method is based on the maximum likelihood (ML) criterion and includes output error and equation error methods as special cases. Both the linear and nonlinear models with and without process noise are considered. The flight test data from lateral maneuvers of HL-10 and M2/F3 lifting bodies are processed to determine the lateral stability and control derivatives, instrumentation accuracies and biases. A comparison is made between the results of the output error method and the generalized ML method for M2/F3 data containing gusts. It is shown that better fits to time histories are obtained by using the generalized ML method.
    Keywords: AIRCRAFT
    Type: Joint Automatic Control Conference; Aug 16, 1972 - Aug 18, 1972; Stanford, CA
    Format: text
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  • 5
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    Maximum likelihood identification and optimal input design for identifying aircraft stability and control derivatives (1973)
    In:  CASI
    Details
    Publication Date: 2019-06-27
    Description: A new method of extracting aircraft stability and control derivatives from flight test data is developed based on the maximum likelihood cirterion. It is shown that this new method is capable of processing data from both linear and nonlinear models, both with and without process noise and includes output error and equation error methods as special cases. The first application of this method to flight test data is reported for lateral maneuvers of the HL-10 and M2/F3 lifting bodies, including the extraction of stability and control derivatives in the presence of wind gusts. All the problems encountered in this identification study are discussed. Several different methods (including a priori weighting, parameter fixing and constrained parameter values) for dealing with identifiability and uniqueness problems are introduced and the results given. The method for the design of optimal inputs for identifying the parameters of linear dynamic systems is also given. The criterion used for the optimization is the sensitivity of the system output to the unknown parameters. Several simple examples are first given and then the results of an extensive stability and control dervative identification simulation for a C-8 aircraft are detailed.
    Keywords: AIRCRAFT
    Type: NASA-CR-2200
    Format: application/pdf
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