scholarly journals A Data-Driven Approach to Identify Flight Test Data Suitable to Design Angle of Attack Synthetic Sensor for Flight Control Systems

Aerospace ◽  
2020 ◽  
Vol 7 (5) ◽  
pp. 63 ◽  
Author(s):  
Angelo Lerro ◽  
Alberto Brandl ◽  
Manuela Battipede ◽  
Piero Gili
Keyword(s):  
Control Systems ◽  
Test Data ◽  
Flight Control ◽  
Flight Test ◽  
Data Driven ◽  
Training Set ◽  
Consequent Reduction ◽  
Data Driven Approach ◽  
Data Points ◽  
Data Pruning

Digital avionic solutions enable advanced flight control systems to be available also on smaller aircraft. One of the safety-critical segments is the air data system. Innovative architectures allow the use of synthetic sensors that can introduce significant technological and safety advances. The application to aerodynamic angles seems the most promising towards certified applications. In this area, the best procedures concerning the design of synthetic sensors are still an open question within the field. An example is given by the MIDAS project funded in the frame of Clean Sky 2. This paper proposes two data-driven methods that allow to improve performance over the entire flight envelope with particular attention to steady state flight conditions. The training set obtained is considerably undersized with consequent reduction of computational costs. These methods are validated with a real case and they will be used as part of the MIDAS life cycle. The first method, called Data-Driven Identification and Generation of Quasi-Steady States (DIGS), is based on the (i) identification of the lift curve of the aircraft; (ii) augmentation of the training set with artificial flight data points. DIGS’s main aim is to reduce the issue of unbalanced training set. The second method, called Similar Flight Test Data Pruning (SFDP), deals with data reduction based on the isolation of quasi-unique points. Results give an evidence of the validity of the methods for the MIDAS project that can be easily adopted for generic synthetic sensor design for flight control system applications.

AUTOMATED GENERATION OF TEST TRAJECTORIES FOR EMBEDDED FLIGHT CONTROL SYSTEMS

2002 ◽  
Vol 12 (02) ◽  
pp. 175-200 ◽  
Author(s):  
BOJAN CUKIC ◽  
BRIAN J. TAYLOR ◽  
HARSHINDER SINGH
Keyword(s):  
Linear Regression ◽  
Control Systems ◽  
Test Data ◽  
Flight Control ◽  
Performance Metrics ◽  
Large Set ◽  
Data Generation ◽  
Statistical Regression ◽  
Automated Generation ◽  
Independent Variables

Automated generation of test cases is a prerequisite for fast testing. Whereas the research in automated test data generation addressed the creation of individual test points, test trajectory generation has attracted limited attention. In simple terms, a test trajectory is defined as a series of data points, with each (possibly multidimensional) point relying upon the value(s) of previous point(s). Many embedded systems use data trajectories as inputs, including closed-loop process controllers, robotic manipulators, nuclear monitoring systems, and flight control systems. For these systems, testers can either handcraft test trajectories, use input trajectories from older versions of the system or, perhaps, collect test data in a high fidelity system simulator. While these are valid approaches, they are expensive and time-consuming, especially if the assessment goals require many tests. We developed a framework for expanding a small, conventionally developed set of test trajectories into a large set suitable, for example, for system safety assurance. Statistical regression is the core of this framework. The regression analysis builds a relationship between controllable independent variables and closely correlated dependent variables, which represent test trajectories. By perturbing the independent variables, new test trajectories are generated automatically. Our approach has been applied in the safety assessment of a fault tolerant flight control system. Linear regression, multiple linear regression, and autoregressive techniques are compared. The performance metrics include the speed of test generation and the percentage of "acceptable" trajectories, measured by the domain specific reasonableness checks.

scholarly journals A Data-Driven Approach to Detect Faults in the Airbus Flight Control System

2016 ◽  
Vol 49 (17) ◽  
pp. 52-57 ◽  
Author(s):  
Philippe Goupil ◽  
Simone Urbano ◽  
Jean-Yves Tourneret
Keyword(s):  
Control System ◽  
Flight Control ◽  
Data Driven ◽  
Flight Control System ◽  
Data Driven Approach

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.

Multi sensor data fusion based approach for the calibration of airdata systems

2011 ◽  
Vol 115 (1164) ◽  
pp. 113-122 ◽  
Author(s):  
M. Majeed ◽  
I. N. Kar
Keyword(s):  
Kalman Filter ◽  
Data Fusion ◽  
Test Data ◽  
Flight Control ◽  
Unscented Kalman Filter ◽  
Flight Test ◽  
Sensor Data ◽  
Sensor Data Fusion ◽  
Multi Sensor Data Fusion ◽  
Fusion Methods

AbstractAccurate and reliable airdata systems are critical for aircraft flight control system. In this paper, both extended Kalman filter (EKF) and unscented Kalman filter (UKF) based various multi sensor data fusion methods are applied to dynamic manoeuvres with rapid variations in the aircraft motion to calibrate the angle-of-attack (AOA) and angle-of-sideslip (AOSS) and are compared. The main goal of the investigations reported is to obtain online accurate flow angles from the measured vane deflection and differential pressures from probes sensitive to flow angles even in the adverse effect of wind or turbulence. The proposed algorithms are applied to both simulated as well as flight test data. Investigations are initially made using simulated flight data that include external winds and turbulence effects. When performance of the sensor fusion methods based on both EKF and UKF are compared, UKF is found to be better. The same procedures are then applied to flight test data of a high performance fighter aircraft. The results are verified with results obtained using proven an offline method, namely, output error method (OEM) for flight-path reconstruction (FPR) using ESTIMA software package. The consistently good results obtained using sensor data fusion approaches proposed in this paper establish that these approaches are of great value for online implementations.

Research on the Flight Control for an Asymmetrical X-Quadrotor

2013 ◽  
Vol 313-314 ◽  
pp. 399-402
Author(s):  
Yong Jun Ding ◽  
Xiang Zhou Wang ◽  
Shu Hua Zheng
Keyword(s):  
Test Data ◽  
Dynamic Characteristics ◽  
Flight Control ◽  
Control Method ◽  
Flight Test ◽  
Control Algorithms ◽  
Quick Response ◽  
Asymmetrical Structure ◽  
Control Forces ◽  
Outer Environment

The paper presents an asymmetrical structure of X-quadrotor, which is different from the traditional quadrotor and is more complicated in the analysis of control forces and moments. A novel control method based on backstepping is applied in the attitude loop. And the compensation for perturbations of outer environment and noise of the measurements has been done. Then, various simulations are performed and the results show the system has a quick response with small overshoot and good dynamic characteristics. Finally, the experiments are implemented on the prototype. The flight test data has validated the robustness of the control algorithms.

scholarly journals Transient-optimised real-bogus classification with Bayesian Convolutional Neural Networks — sifting the GOTO candidate stream

2021 ◽  
Author(s):  
T L Killestein ◽  
J Lyman ◽  
D Steeghs ◽  
K Ackley ◽  
M J Dyer ◽  
...  
Keyword(s):  
Large Scale ◽  
Data Driven ◽  
Wide Field ◽  
Data Generation ◽  
Training Set ◽  
Transient Sources ◽  
Data Driven Approach ◽  
Model Training ◽  
Difference Imaging

Abstract Large-scale sky surveys have played a transformative role in our understanding of astrophysical transients, only made possible by increasingly powerful machine learning-based filtering to accurately sift through the vast quantities of incoming data generated. In this paper, we present a new real-bogus classifier based on a Bayesian convolutional neural network that provides nuanced, uncertainty-aware classification of transient candidates in difference imaging, and demonstrate its application to the datastream from the GOTO wide-field optical survey. Not only are candidates assigned a well-calibrated probability of being real, but also an associated confidence that can be used to prioritise human vetting efforts and inform future model optimisation via active learning. To fully realise the potential of this architecture, we present a fully-automated training set generation method which requires no human labelling, incorporating a novel data-driven augmentation method to significantly improve the recovery of faint and nuclear transient sources. We achieve competitive classification accuracy (FPR and FNR both below 1%) compared against classifiers trained with fully human-labelled datasets, whilst being significantly quicker and less labour-intensive to build. This data-driven approach is uniquely scalable to the upcoming challenges and data needs of next-generation transient surveys. We make our data generation and model training codes available to the community.

Virtual Reference Feedback Tuning for Cascade Control Systems

2016 ◽  
Vol 28 (5) ◽  
pp. 739-744 ◽  
Author(s):  
Huy Quang Nguyen ◽  
◽  
Osamu Kaneko ◽  
Yoshihiko Kitazaki ◽  
Keyword(s):  
Control Systems ◽  
Cascade Control ◽  
Data Driven ◽  
Experiment Data ◽  
Feedback Controllers ◽  
Virtual Reference ◽  
Text Data ◽  
Tuning Method ◽  
Data Driven Approach ◽  
The Cost

[abstFig src='/00280005/17.jpg' width='300' text='Data-driven approach to cascade control systems' ] Virtual Reference Feedback Tuning (VRFT), proposed by Campi et al., is an effective data-driven tuning method used in feedback controllers because the desired parameters implemented in the controller are obtained by using only one-shot experiment data. In this paper, we apply VRFT to cascade control systems. We also discuss the meaning of the cost function to be minimized. A numerical example is demonstrated to show an effectiveness and validity of our proposed method.

scholarly journals A Review of Wind Tunnel Based Virtual Flight Testing Techniques for Evaluation of Flight Control Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-22 ◽  
Author(s):  
Min Huang ◽  
Zhong-wei Wang
Keyword(s):  
Wind Tunnel ◽  
Control Systems ◽  
Flight Control ◽  
Wind Tunnel Test ◽  
Flight Test ◽  
Evaluation Methods ◽  
Test System ◽  
Hardware In The Loop ◽  
Flight Testing ◽  
Testing Techniques

Wind tunnel based Virtual Flight Testing (VFT) is a dynamic wind tunnel test for evaluating flight control systems (FCS) proposed in recent decades. It integrates aerodynamics, flight dynamics, and FCS as a whole and is a more realistic and reliable method for FCS evaluation than traditional ground evaluation methods, such as Hardware-in-the-Loop Simulation (HILS). With FCS evaluated by VFT before flight test, the risk of flight test will be further reduced. In this paper, the background, progress, and prospects of VFT are systematically summarized. Specifically, the differences among VFT, traditional dynamic wind tunnel methods, and traditional FCS evaluation methods are introduced in order to address the advantages of evaluating FCS with VFT. Secondly, the progress of VFT is reviewed in detail. Then, the test system and key technologies of VFT for FCS evaluation are analyzed. Lastly, the prospects of VFT for evaluating FCS are described.

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