Practical Aspects of the Equation-Error Method for Aircraft Parameter Estimation

Morelli, Eugene A.

doi:10.2514/6.2006-6144

Cited by 97 publications

(95 citation statements)

References 3 publications

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“…The computed error bounds from the FTR method accurately characterized these differences, which is consistent with similar findings in previous work [6,13]. Although such a measure is easy to compute postflight (when the converged values are known), metrics that can be computed in real time must be devised.…”

Section: Model Validitysupporting

confidence: 72%

“…Explanations of why the estimated parameter standard errors are computed in this way, and why this calculation in the frequency domain produces parameter error measures that are consistent with the scatter in parameter estimates from repeated maneuvers, can be found in [6]. Realistic simulation testing has shown that the accuracy of model parameters estimated with this method is comparable to using a time-domain output-error method employing iterative nonlinear optimization in postflight analysis, for which all the data are available [13].…”

Section: B Real-time Parameter Estimation In the Frequency Domainmentioning

confidence: 80%

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Real-Time Dynamic Modeling: Data Information Requirements and Flight-Test Results

Morelli

Smith

2009

Journal of Aircraft

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Practical aspects of identifying dynamic models for aircraft in real time were studied. Topics included the formulation of an equation-error method in the frequency domain to estimate nondimensional stability and control derivatives in real time, data information content for accurate modeling results, speed of convergence, and data information management techniques such as data forgetting, incorporating prior information, and optimized excitation. Real-time dynamic modeling was applied to simulation data and flight-test data from a modified F-15B fighter aircraft and to operational flight data from a subscale jet transport aircraft. Estimated parameter standard errors, prediction cases, and comparisons with results from postflight analysis using the output-error method in the time domain were used to demonstrate the accuracy of the identified real-time models.Nomenclature a x , a y , a z = body-axis translational accelerometer measurements, g or ft=s

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Section: Model Validitysupporting

confidence: 72%

Section: B Real-time Parameter Estimation In the Frequency Domainmentioning

confidence: 80%

Real-Time Dynamic Modeling: Data Information Requirements and Flight-Test Results

Morelli

Smith

2009

Journal of Aircraft

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“…Because aircraft parameter estimation is often associated with data collinearity [25], a biased parameter estimation technique known as Principal Components Regression (PRC) was used. PCR is able to increase the accuracy of the parameter estimates in case of multi-collinearity among the predictor variables [20].…”

Section: Parameter Estimationmentioning

confidence: 99%

Terrain Relative Navigation for Planetary Landing Using Stereo Vision Measurements Obtained from Hazard Mapping

Woicke

Mooij

2017

Advances in Aerospace Guidance, Navigation and Control

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As a result of new aviation legislation, from 2019 on all air-carrier pilots are obliged to go through flight simulator-based stall recovery training. For this reason the Control and Simulation division at Delft University of Technology has set up a task force to develop a new methodology for high-fidelity aircraft stall behavior modeling and simulation. As part of this research project, the development of a new high-fidelity Cessna II simulation model, valid throughout the normal, pre-stall flight envelope, is presented in this paper. From an extensive collection of flight test data, aerodynamic model identification was performed using the Two-Step Method. New in this approach is the use of the Unscented Kalman Filter for an improved accuracy and robustness of the state estimation step. Also, for the first time an explicit data-driven model structure selection is presented for the Citation II by making use of an orthogonal regression scheme. This procedure has indicated that most of the six non-dimensional forces and moments can be parametrized sufficiently by a linear model structure. It was shown that only the translational and lateral aerodynamic force models would benefit from the addition of higher order terms, more specifically the squared angle of attack and angle of sideslip. The newly identified aerodynamic model was implemented into an upgraded version of the existing simulation framework and will serve as a basis for the integration of a stall and post-stall model.

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“…[1] provides a thorough description of this method (among others), along with information on how the method can be applied in practice and the MATLAB ® software that implements it. Using equation-error in the frequency domain has been shown 12 to produce modeling results comparable in accuracy to using iterative nonlinear optimization in a conventional output-error approach in the time domain, but requires much less computation and therefore is faster and easier to use. In fact, many of the modeling results presented here were computed in real time during the flight tests, using a real-time formulation of equation-error parameter estimation in the frequency domain 1,6,13 .…”

Section: Introductionmentioning

confidence: 99%

Flight Test Maneuvers for Efficient Aerodynamic Modeling

Morelli

2012

Journal of Aircraft

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Novel flight test maneuvers for efficient aerodynamic modeling were developed and demonstrated in flight. Orthogonal optimized multi-sine inputs were applied to aircraft control surfaces to excite aircraft dynamic response in all six degrees of freedom simultaneously, while keeping the aircraft close to chosen reference flight conditions. Each maneuver was designed for a specific modeling task that cannot be adequately or efficiently accomplished using conventional flight test maneuvers. Each maneuver is described and explained, then demonstrated on a subscale jet transport aircraft in flight. Real-time and post-flight modeling results from equation-error parameter estimation in the frequency domain were used to show the effectiveness and efficiency of the maneuvers, as well as the quality of the aerodynamic models that can be identified from the resultant flight data. Nomenclature

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Practical Aspects of the Equation-Error Method for Aircraft Parameter Estimation

Cited by 97 publications

References 3 publications

Real-Time Dynamic Modeling: Data Information Requirements and Flight-Test Results

Real-Time Dynamic Modeling: Data Information Requirements and Flight-Test Results

Terrain Relative Navigation for Planetary Landing Using Stereo Vision Measurements Obtained from Hazard Mapping

Flight Test Maneuvers for Efficient Aerodynamic Modeling

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