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Comparison of Flight Parameters in SIL Simulation Using Commercial Autopilots and X-Plane Simulator for Multi-Rotor Models
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Comparison of Flight Parameters in SIL Simulation Using Commercial Autopilots and X-Plane Simulator for Multi-Rotor Models
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Comparison of Flight Parameters in SIL Simulation Using Commercial Autopilots and X-Plane Simulator for Multi-Rotor Models
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Journal Article
Comparison of Flight Parameters in SIL Simulation Using Commercial Autopilots and X-Plane Simulator for Multi-Rotor Models
2024
Overview
Modern aviation technology development heavily relies on computer simulations. SIL (Software-In-The-Loop) simulations are essential for evaluating autopilots and control algorithms for multi-rotors, including drones and other UAVs (Unmanned Aerial Vehicle). In such simulations, it is possible to compare the flight parameters achieved by flying platforms using various commercial autopilots widely used in the UAV sector. This research aims to provide objective and comprehensive insights into the effectiveness of different autopilot systems This article examines the simulated flight test results of a drone performing the same mission using different autopilot systems. The X-Plane software was used as an environment to simulate the dynamics of the drone and its surroundings. Matlab/Simulink r2023a provided the interface between autopilot software and X-Plane models. Those methods allowed us to obtain an appropriate comparison of the autopilot systems and indicate the main differences between them. This research focused on analyzing UAV flight characteristics such as stability, trajectory tracking, response time to control changes, and the overall effectiveness of autopilots. Various flight scenarios including take-off, landing, flight at a constant altitude, dynamic manoeuvrers and, flight along a planned trajectory were also examined. In order to obtain the most accurate and realistic results, the tests were carried out in various weather conditions. The aim of this research is to provide objective data and analysis to compare the performance of commercial autopilots. This method offers several advantages, including cost-effective testing, the ability to test in diverse environmental conditions, and the evaluation of autopilot algorithms without the need for real hardware. The findings of this study may have a considerable impact on how autopilot designers and developers choose the best platforms and technologies for their projects. Future research on this topic will compare the obtained data with flight test data.
