Maximum likelihood identification of a rotary-wing RPV simulation model from flight-test data

Author(s):  
P. Bruce ◽  
J. Silva ◽  
M. Kellett
2014 ◽  
Vol 602-605 ◽  
pp. 3202-3205
Author(s):  
Xu Sheng Gan ◽  
Xue Qin Tang ◽  
Hai Long Gao

To accurately identify the nonlinear model for aircraft, maximum likelihood method is introduced to analyze the flight test data for compatibility check, which can satisfy the kinematics equations of aircraft at the same time. The experiment shows that the proposed method has a good compatibility check effect, and it is also effective and feasible for flight test data for aircraft.


2021 ◽  
pp. 1-22
Author(s):  
L.V.T. Nguyen ◽  
M. Tyan ◽  
J.-W. Lee ◽  
S. Kim

Abstract This paper proposes a procedure to improve the accuracy of the light aircraft 6 DOF simulation model by implementing model tuning and aerodynamic database correction using flight test data. In this study, the full-scale flight testing of a 2-seater aircraft has been performed in specific longitudinal manoeuver for model enhancement and simulation validation purposes. The baseline simulation model database is constructed using multi-fidelity analysis methods such as wind tunnel (W/T) test, computational fluid dynamic (CFD) and empirical calculation. The enhancement process starts with identifying longitudinal equations of motion for sensitivity analysis, where the effect of crucial parameters is analysed and then adjusted using the model tuning technique. Next, the classical Maximum Likelihood (ML) estimation method is applied to calculate aerodynamic derivatives from flight test data, these parameters are utilised to correct the initial aerodynamic table. A simulation validation process is introduced to evaluate the accuracy of the enhanced 6 DOF simulation model. The presented results demonstrate that the applied enhancement procedure has improved the simulation accuracy in longitudinal motion. The discrepancy between the simulation and flight test response showed significant improvement, which satisfies the regulation tolerance.


2021 ◽  
Author(s):  
Sven Marschalk ◽  
Peter C. Luteijn ◽  
Dirk van Os ◽  
Daan M. Pool ◽  
Coen C. de Visser
Keyword(s):  

Author(s):  
Dheeraj Agarwal ◽  
Linghai Lu ◽  
Gareth D. Padfield ◽  
Mark D. White ◽  
Neil Cameron

High-fidelity rotorcraft flight simulation relies on the availability of a quality flight model that further demands a good level of understanding of the complexities arising from aerodynamic couplings and interference effects. One such example is the difficulty in the prediction of the characteristics of the rotorcraft lateral-directional oscillation (LDO) mode in simulation. Achieving an acceptable level of the damping of this mode is a design challenge requiring simulation models with sufficient fidelity that reveal sources of destabilizing effects. This paper is focused on using System Identification to highlight such fidelity issues using Liverpool's FLIGHTLAB Bell 412 simulation model and in-flight LDO measurements from the bare airframe National Research Council's (Canada) Advanced Systems Research Aircraft. The simulation model was renovated to improve the fidelity of the model. The results show a close match between the identified models and flight test for the LDO mode frequency and damping. Comparison of identified stability and control derivatives with those predicted by the simulation model highlight areas of good and poor fidelity.


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