Automatic control education using FlightGear and MATLAB based virtual lab

Moness, Mohammed; Mostafa, Ayman Mohammed; Abdel-Fadeel, M. A.; Aly, A. I.; Al-Shamandy, A.

doi:10.21608/iceeng.2012.31372

Cited by 5 publications

(2 citation statements)

References 3 publications

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“…When the aircraft model is well-generated with a highly accurate database, it is important to evaluate the reliability of the flight simulation model. Different procedures and validation methodologies have been proposed based on numerous flight simulation platforms such as JSBSim, Matlab/Simulink or X-Plane simulator (19)(20)(21)(22) . Leong et al (22) described the evaluation of three different modelling and simulation techniques to support UAV development for glacial ice research.…”

Section: Introductionmentioning

confidence: 99%

Enhancement of light aircraft 6 DOF simulation using flight test data in longitudinal motion

et al. 2021

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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.

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Section: Introductionmentioning

confidence: 99%

Enhancement of light aircraft 6 DOF simulation using flight test data in longitudinal motion

et al. 2021

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“…The possibility to visualize the simulation in a detailed 3D environment is obtained thanks to an interface with the open-source flight simulator FlightGear [11], [12], [13], as shown in Fig. 1.…”

Section: Introductionmentioning

confidence: 99%

APRICOT: Aerospace PRototypIng COntrol Toolbox. A Modeling and Simulation Environment for Aircraft Control Design

Ferrarelli

Caporale

Settimi

et al. 2016

Modelling and Simulation for Autonomous Systems

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A novel MATLAB/Simulink based modeling and simulation environment for the design and rapid prototyping of state-of-the-art aircraft control systems is proposed. The toolbox, named APRICOT, is able to simulate the longitudinal and laterodirectional dynamics of an aircraft separately, as well as the complete 6 degrees of freedom dynamics. All details of the dynamics can be easily customized in the toolbox, some examples are shown in the paper. Moreover, different aircraft models can be easily integrated. The main goal of APRICOT is to provide a simulation environment to test and validate different control laws with different aircraft models. Hence, the proposed toolbox has applicability both for educational purposes and control rapid prototyping. With respect to similar software packages, APRICOT is customizable in all its aspects, and has been released as open source software. An interface with Flightgear Simulator allows for online visualization of the flight. Examples of control design with simulation experiments are reported and commented.

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