Optimization of UAV Flight Control Algorithm and Flight Simulation in Two-dimension

2020 
Large-scale Unmanned Aerial Vehicle (UAV) groups flight simulation in two-dimensional planes is commonly applied to UAV cluster mission planning algorithm design. In this paper, an UAV control algorithm optimized for two-dimensional planes is designed. The tandem structure of closed loops, as well as the control laws of L1 and Total Energy Control System (TECS), are transplanted to an UAV model that is simplified to a moving particle of a two-dimensional space, and UAV flight simulation is performed based on the flight control algorithm. Compared with the traditional 3D space flight simulation, it can save hardware resources and improve the simulation efficiency. Compare with the flight simulation based on the geometric method, on the premise of maintaining the dynamics basis, the trajectory and dynamics curves are closer to the actual flight results in 3D space, and the dynamics data onto the entire flight can be recorded. It has been verified that 50 UAVs need only 0.8s to perform 100 square-area snake-like search simulation experiments, and the fitting degree of the UAV's flight curve to the three-dimensional space is greater than 80%. The two-dimensional plane flight control algorithm and flight simulation proposed in this paper provide a new simulation method for the design of UAV cluster mission planning algorithms, therefore can help promote the development of the subject.
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