In: 2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (2015). Ĭhen, J., Xiao, G.: Research on aircraft longitudinal flight control law identification based on QAR data. Īschauer, G., et al.: Co-simulation of Matlab and flightGear for identification and control of aircraft. American Institute of Aeronautics and Astronautics, Virtual Event (2021). Sagliano, M.: Open-source visualization of reusable rockets motion: approaching simulink-flightgear co-simulation. In: 2020 28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), pp. Zhang, M., et al.: Automation of high-fidelity CFD analysis for aircraft design and optimization aided by HPC. Stevens., et al.: Aircraft Control and Simulation. L’Afflitto, Andrea: A Mathematical Perspective on Flight Dynamics and Control. The simulation results prove the rationality of the flight dynamics model and effectiveness of the designed flight control system and visual simulation platform. The linear model and longitudinal control law is then studied based on this platform. In this paper, we first developed a high-fidelity flight dynamics nonlinear model and established a complete visual simulation platform for a specific type of aircraft. As for these challenges, In addition to more accurate dynamic modeling of the airframe, new methods such as scene simulation or semi-physical technology must be used to improve the R &D efficiency. IB Gksel Electrofluidsystems offers engineering services to develop realistic MATLAB-Simulink-FlightGear models for single and multi UAV flight simulations. For example, the developed subsystems are difficult to put into the whole aircraft level for analysis, and interpreting flight modes is not a straightforward matter. With the increasingly requirements for flight performance and automation level of modern civil aviation aircraft, there are many difficulties in the R &D of flight control system’s soft and hardware.
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