Modelling and Simulation of Small Scale Fixed-Wing Autonomous Aerial Vehicles

KHAN, Mahmud Safat (2021). Modelling and Simulation of Small Scale Fixed-Wing Autonomous Aerial Vehicles. Doctoral, Sheffield Hallam University.

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Link to published version:: https://doi.org/10.7190/shu-thesis-00465
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    Abstract

    Although various tools (e.g., Wind tunnels, Professional-grade CFD packages, Industrial Grade Flight Simulators, etc.) for aid in the development of fixed-wing UAV/UASs exists, the associated high costs and skills requirements stunt adequate development work for many students, researchers, and even prospective businesses. The aim of this thesis, therefore, is to present investigations of effective modelling techniques, improvement of simulation fidelity, exploration and demonstration of alternative simulation and modelling approaches. The approach taken in conducting all the relevant work factored in the use of free and openly available tools and code to provide solutions for higher fidelity simulation and modelling without reliance on the traditional expensive methods. MATLAB/Simulink has been utilized to develop a 12 state, 6 degrees of freedom simulation. A scaled down Remote Control model aircraft (FMS SkyTrainer 182) and a widely used commercial off-the-shelf (COTS) simulator (X-Plane) was used to demonstrate alternative modelling techniques. Techniques to improve X-Plane’s modelling and simulation fidelity for small scale UAVs are demonstrated. Processes for improving aerodynamic lift-modelling inputs for the MATLAB/Simulink codes are outlined. Application of the free and open source XFLR5 program for supplying better aerodynamic/stability/control data for modelling is demonstrated. The work undertaken in all the aforementioned areas collectively establish an approach to simulation and modelling of small scale fixed-wing UAVs/UASs that improves simulation fidelity without the reliance on expensive facilities or software solutions.

    Item Type: Thesis (Doctoral)
    Additional Information: Director of Studies: Dr Jonathan Potts Supervisor: Dr Lyuba Alboul
    Research Institute, Centre or Group - Does NOT include content added after October 2018: Sheffield Hallam Doctoral Theses
    Identification Number: https://doi.org/10.7190/shu-thesis-00465
    Depositing User: Justine Gavin
    Date Deposited: 17 Aug 2022 14:27
    Last Modified: 17 Aug 2022 14:27
    URI: https://shura.shu.ac.uk/id/eprint/30601

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