scholarly journals Output Error Method for Tiltrotor Unstable in Hover

2017 ◽  
Vol 64 (1) ◽  
pp. 23-36 ◽  
Author(s):  
Piotr Lichota ◽  
Joanna Szulczyk
Keyword(s):  
System Identification ◽  
Flight Test ◽  
Model Parameters ◽  
Output Error ◽  
Control Derivatives ◽  
Time Histories ◽  
System Output ◽  
The Time Domain ◽  
And Control ◽  
Error Method

Abstract This article investigates unstable tiltrotor in hover system identification from flight test data. The aircraft dynamics was described by a linear model defined in Body-Fixed-Coordinate System. Output Error Method was selected in order to obtain stability and control derivatives in lateral motion. For estimating model parameters both time and frequency domain formulations were applied. To improve the system identification performed in the time domain, a stabilization matrix was included for evaluating the states. In the end, estimates obtained from various Output Error Method formulations were compared in terms of parameters accuracy and time histories. Evaluations were performed in MATLAB R2009b environment.

scholarly journals Flight Path Reconstruction and Parameter Estimation Using Output-Error Method

2006 ◽  
Vol 13 (4-5) ◽  
pp. 379-392 ◽  
Author(s):  
Benedito Carlos de Oliveira Maciel ◽  
Luiz Carlos Sandoval Góes ◽  
Elder Moreira Hemerly ◽  
Nei Salis Brasil Neto
Keyword(s):  
Test Data ◽  
Inertial Sensors ◽  
Flight Test ◽  
Flight Path ◽  
Positioning Systems ◽  
Output Error ◽  
Control Derivatives ◽  
And Control ◽  
Derivatives Of ◽  
Error Method

This work describes the application of the output-error method using the Levenberg-Marquardt optimization algorithm to the Flight Path Reconstruction (FPR) problem, which constitutes an important preliminary step towards the aircraft parameter identification. This method is also applied to obtain the aerodynamic and control derivatives of a regional jet aircraft from flight test data with measurement noise and bias. Experimental results are reported, employing a real jet aircraft, with flight test data acquired by smart probes, inertial sensors (gyrometers and accelerometers) and Global Positioning Systems (GPS) receivers.

scholarly journals Results of Short-Period Helicopter System Identification Using Output-Error and Hybrid Search-Gradient Optimization Algorithm

2010 ◽  
Vol 2010 ◽  
pp. 1-17 ◽  
Author(s):  
Ronaldo Vieira Cruz ◽  
Luiz Carlos Sandoval Góes
Keyword(s):  
System Identification ◽  
Flight Test ◽  
Identification Problem ◽  
Hybrid Search ◽  
Output Error ◽  
Aerodynamic Derivatives ◽  
Gradient Optimization ◽  
Short Period ◽  
Test Instrumentation ◽  
The Time Domain

This article focuses on the problem of parameter estimation of the uncoupled, linear, short-period aerodynamic derivatives of a “Twin Squirrel” helicopter in level flight and constant speed. A flight test campaign is described with respect to maneuver specification, flight test instrumentation, and experimental data collection used to estimate the aerodynamic derivatives. The identification problem is solved in the time domain using the output-error approach, with a combination of Genetic Algorithm (GA) and Levenberg-Marquardt optimization algorithms. The advantages of this hybrid GA and gradient-search methodology in helicopter system identification are discussed.

scholarly journals Method for designing multi-input system identification signals using a compact time-frequency representation

2021 ◽  
Author(s):  
Mathias Stefan Roeser ◽  
Nicolas Fezans
Keyword(s):  
System Identification ◽  
Design Method ◽  
Flight Test ◽  
Compact Representation ◽  
Time Frequency ◽  
Stability And Control ◽  
Frequency Representation ◽  
Aerodynamic Parameters ◽  
Definition Of ◽  
And Control

AbstractA flight test campaign for system identification is a costly and time-consuming task. Models derived from wind tunnel experiments and CFD calculations must be validated and/or updated with flight data to match the real aircraft stability and control characteristics. Classical maneuvers for system identification are mostly one-surface-at-a-time inputs and need to be performed several times at each flight condition. Various methods for defining very rich multi-axis maneuvers, for instance based on multisine/sum of sines signals, already exist. A new design method based on the wavelet transform allowing the definition of multi-axis inputs in the time-frequency domain has been developed. The compact representation chosen allows the user to define fairly complex maneuvers with very few parameters. This method is demonstrated using simulated flight test data from a high-quality Airbus A320 dynamic model. System identification is then performed with this data, and the results show that aerodynamic parameters can still be accurately estimated from these fairly simple multi-axis maneuvers.

Rotorcraft Lateral-Directional Oscillations: The Anatomy of a Nuisance Mode

2021 ◽  
Author(s):  
Dheeraj Agarwal ◽  
Linghai Lu ◽  
Gareth D. Padfield ◽  
Mark D. White ◽  
Neil Cameron
Keyword(s):  
Simulation Model ◽  
Simulation Models ◽  
Flight Test ◽  
Flight Simulation ◽  
Stability And Control ◽  
Systems Research ◽  
Control Derivatives ◽  
Research Aircraft ◽  
Level Of Understanding ◽  
And Control

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.

Spinning gasodynamic projectile system identification experiment design

2020 ◽  
Vol 92 (3) ◽  
pp. 452-459 ◽  
Author(s):  
Piotr Lichota ◽  
Mariusz Jacewicz ◽  
Joanna Szulczyk
Keyword(s):  
System Identification ◽  
High Speed ◽  
Content Type ◽  
Stability And Control ◽  
Novel Approach ◽  
Control Derivatives ◽  
Designed Experiment ◽  
Regions Of Stability ◽  
Short Time ◽  
And Control

Purpose The purpose of this paper is to present the methodology that was used to design a system identification experiment of a generic spinning gasodynamic projectile. For this object, because the high-speed spinning motion, it was not possible to excite the aircraft motion along body axes independently. Moreover, it was not possible to apply simultaneous multi-axes excitations because of the short time in which system identification experiments can be performed (multi-step inputs) or because it is not possible to excite the aircraft with a complex input (multi-sine signals) because of the impulse gasodynamic engines (lateral thrusters) usage. Design/methodology/approach A linear projectile model was used to obtain information about identifiability regions of stability and control derivatives. On this basis various sets of lateral thrusters’ launching sequences, imitating continuous multi-step inputs were used to excite the nonlinear projectile model. Subsequently, the nonlinear model for each excitation set was identified from frequency responses, and the results were assessed. For comparison, the same approach was used for the same projectile exited with aerodynamic controls. Findings It was found possible to design launching sequences of lateral thrusters that imitate continuous multi-step input and allow to obtain accurate system identification results in specified frequency range. Practical implications The designed experiment can be used during polygonal shooting to obtain a true projectile aerodynamic model. Originality/value The paper proposes a novel approach to gasodynamic projectiles system identification and can be easily applied for similar cases.

scholarly journals ESTIMATION OF THE LATERAL AERODYNAMIC COEFFICIENTS FOR SKYWALKER X8 FLYING WING FROM REAL FLIGHT-TEST DATA

2018 ◽  
Vol 58 (2) ◽  
pp. 77
Author(s):  
Rahman Mohammadi Farhadi ◽  
Vyacheslav Kortunov ◽  
Andrii Molchanov ◽  
Tatiana Solianyk
Keyword(s):  
Test Data ◽  
Flight Test ◽  
Least Square ◽  
Stability And Control ◽  
Information Parameter ◽  
Control Derivatives ◽  
Aerial Vehicle ◽  
Aerodynamic Parameters ◽  
Priori Information ◽  
And Control

Stability and control derivatives of Skywalker X8 flying wing from flight-test data are estimated by using the combination of the output error and least square methods in the presence of the wind. Data is collected from closed loop flight tests with a proportional-integral-derivative (PID) controller that caused data co-linearity problems for the identification of the unmanned aerial vehicle (UAV) dynamic system. The data co-linearity problem is solved with a biased estimation via priori information, parameter fixing and constrained optimization, which uses analytical values of aerodynamic parameters, the level of the identifiability and sensitivity of the measurement vector to the parameters. Estimated aerodynamic parameters are compared with the theoretically calculated coefficients of the UAV, moreover, the dynamic model is validated with additional flight-test data and small covariances of the estimated parameters.

scholarly journals Identification of Aeroelastic Models for the X-56A Longitudinal Dynamics Using Multisine Inputs and Output Error in the Frequency Domain

Aerospace ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 24 ◽  
Author(s):  
Jared Grauer ◽  
Matthew Boucher
Keyword(s):  
System Identification ◽  
Test Data ◽  
Flight Control ◽  
Fourier Transforms ◽  
Flight Dynamics ◽  
Flight Test ◽  
Multiple Control ◽  
Output Error ◽  
Short Period ◽  
Flight Dynamics Model

System identification from measured flight test data was conducted using the X-56A aeroelastic demonstrator to identify a longitudinal flight dynamics model that included the short period, first symmetric wing bending, and first symmetric wing torsion modes. Orthogonal phase-optimized multisines were used to simultaneously excite multiple control effectors while a flight control system was active. Non-dimensional stability and control derivatives parameterizing an aeroelastic model were estimated using the output-error approach to match Fourier transforms of measured output response data. The predictive capability of the identified model was demonstrated using other flight test data with different inputs and at a different flight conditions. Modal characteristics of the identified model were explored and compared with other predictions. Practical aspects of the experiment design and system identification analysis, specific to flexible aircraft, are also discussed. Overall, the approach used was successful for identifying aeroelastic flight dynamics models from flight test data.

scholarly journals Multi-Axis Inputs for Identification of a Reconfigurable Fixed-Wing UAV

Aerospace ◽  
2020 ◽  
Vol 7 (8) ◽  
pp. 113
Author(s):  
Piotr Lichota
Keyword(s):  
System Identification ◽  
Optimality Criterion ◽  
Likelihood Principle ◽  
Stability And Control ◽  
Input Design ◽  
Relative Standard ◽  
Control Derivatives ◽  
Flight Controls ◽  
Aircraft System ◽  
And Control

Designing a reconfiguration system for an aircraft requires a good mathematical model of the object. An accurate model describing the aircraft dynamics can be obtained from system identification. In this case, special maneuvers for parameter estimation must be designed, as the reconfiguration algorithm may require to use flight controls separately, even if they usually work in pairs. The simultaneous multi-axis multi-step input design for reconfigurable fixed-wing aircraft system identification is presented in this paper. D-optimality criterion and genetic algorithm were used to design the flight controls deflections. The aircraft model was excited with those inputs and its outputs were recorded. These data were used to estimate stability and control derivatives by using the maximum likelihood principle. Visual match between registered and identified outputs as well as relative standard deviations were used to validate the outcomes. The system was also excited with simultaneous multisine inputs and its stability and control derivatives were estimated with the same approach as earlier in order to assess the multi-step design.

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