Shipborne UAVs (Unmanned Aerial Vehicles) play an irreplaceable role in the future maritime war. Countries around the world have been studying and looking for a safe and economical way of shipborne recovery. In this paper, based on the technical scheme and performance characteristics of shipborne UAV net collision recovery, a multi-layer recovery net device is proposed for shipborne UAV recovery. Based on the motion model of the shipborne UAV, Simulink software was used to simulate the final guidance stage of the UAV. The results show that the multi-layer recovery net of the shipborne UAV can adapt to the error caused by ship rocking in the process, and make up for the tracking error and net collision error of UAV in 3D motion simulation. This device has a broad application prospect and has reference significance for comprehensively improving the recovery efficiency of UAVs.

Backstepping design, neural network technology, robust adaptive control and terminal sliding-mode control is combined. Firstly, neural networks are used to estimate the virtual control laws of the controlled system. Secondly, terminal sliding-mode control is utilized to improve the convergence speed and robustness of the controlled plant. Thirdly, robust adaptive control method is employed to estimate the unknown upper boundary of uncertainties. Lastly, backstepping design is incorporated to design the virtual control laws and actual control law of the controlled system. Based on Lyapunov stability theorem, all of error signals are bounded and exponentially converge to a bound neighbor of the origin. Simulation results show the effectiveness of the proposed control method.

According to these parameters, variable trajectory maneuver of target missiles can realize the best penetration effect, and promote train effect of air defense missile.