Browsing by Author "Hoff, J. C."

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    Aircraft parameter estimation by estimation - before - modelling technique
    (Cranfield University, 1995-11) Hoff, J. C.; Cook, M. V.
    The use of the estímation-before-modellíng (EBM) two step identification procedure for the determination of aircraft aerodynamic derivatives from flight test data is analysed and illustrated. In the first step of the identification procedure the usual Extended Kalman Filter (EKF) associated with the Modified Bryson-Frazíer (MBF) smoother is compared with a new alterative filtering and smoothing process. The new smoother is simpler and less computationally demanding than the MBF smoother. However, its main advantage is that it enables simultaneous data smoothing with state derivative estimation, thereby avoiding the need for a separate differentiation algorithm. The new smoother differentiator has an important feature that is the determination of the noise characteristics of the measurement signal under analysis prior to the smoothing process. This is done by variance matching between the theoretical and measured autocorrelation of the innovation process generated by a Kalman filter. The new technique is compared with the old one by determining the aerodynamic models for a EMB-312 Tucano dutch roll manoeuvre. It is demonstrated that the new smoother may be used to replace the MBF. Otherwise the new technique is used in the analysis of the Handley Page Jetstream-100 aircraft low speed controls free phugoid trying to identify the contribution of the power Variation observed during the phugoid to the stability of the oscillation. Finally the models obtained from the phugoid analysis are reprocessed using the Total Least Square regression and the results are compared with those from the ordinary Least Square formulation.
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    Fortran programs for aircraft parameter identification using the estimation-before-modelling technique
    (1997) Hoff, J. C.
    This report describes five Fortran programs formulated to be used in the Estimation-Before-Modelling (E-B-M) methodology for aircraft parameter estimation. The E-B-M technique is a two step estimation process. In the first step, as formulated in this report, the aircraft states are estimated by using Extended Kalman Filter techniques. In the second step the unknowns aerodynamic derivatives are estimated by linear regression formulated as the Stepwise Regression. The five program comprise two different techniques for state estimation, two algorithms for linear regression and a fixed-lag smoother-differentiator.
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    Initial evaluation of the modified step-wise regression procedure to estimate aircraft stability and control parameters from flight test data
    (1993) Hoff, J. C.
    This report presents the initial results of research in progress in the College of Aeronautics at the Cranfield Institute of Technology. The object of the research is to investigate the use of the Modified Stepwise Regression procedure to estimate aircraft stability and control parameters from flight test data. The Stepwise Regression Method for parameter identification is a procedure that inserts independent variables into a regression model. Each time a new variable is added to the model a regression is performed and the fit is examined when the new variable, or any other previously included variable, may be rejected from the model if non-significant to the fit. The iterative process continues until a satisfactory fit (or model) is obtained.