| Citation: | SHI Y，WAN Z Q，WU Z G，et al. Aerodynamic order reduction method for elastic aircraft flight dynamics simulation[J]. Journal of Beijing University of Aeronautics and Astronautics，2023，49（7）：1689-1706 （in Chinese） doi: 10.13700/j.bh.1001-5965.2021.0510
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We develop an aeroelasticity and flight dynamics simulation model with nonlinear aerodynamic reduced order model for low-speed solar unmanned aerial vehicles under high angle of attack caused by gust. Five aerodynamic reduced-order models are created in light of the aforementioned issues, and their use in simulating flight dynamics is further explored. The reduced order models include the model based on the autoregressive model with eXogenous inputs (ARX) method, multi-wavelet Volterra series method, back propagation (BP) neural network, radial basis function (RBF) neural network and support vector regression. Then the convergence and the generalization ability of the five models are compared, and a new model with high precision and strong generalization ability is proposed, which is a combination of ARX and neural network model. Taking a solar UAV model as an example, combining an aerodynamic reduced order model with a rigid-elastic coupling dynamic equation, the flight dynamics simulation model of elastic aircraft is established. Lastly, the computational fluid dynamics-computational structural dynamics (CFD-CSD) outputs and the outcomes of the simulation model based on linear aerodynamics are compared with the simulation results to determine how the UAV model responds to gusts. The results show that the performance of the elastic aircraft simulation model in aerodynamic prediction and gust response analysis is better than that of the model based on linear aerodynamics and is in good agreement with the CFD-CSD model, and the simulation efficiency is much higher than that of the CFD-CSD analysis.
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