Autonomous control of UAV trajectory based on RHC-Radau method in complex penetration combat environment

Unmanned aerial vehicle (UAV) systems are required to independently make timely and accurate attack and control strategies according to dynamic battlefield situations. To optimize the trajectory control of UAVs for ground penetration combat, a 3-degree-of-freedom model and a dynamic model of UAV were established. Considering the constraints of initial and terminal conditions and flight performance, the penetration combat model under multiple constraints is established. A dynamic radar cross section (RCS) threat model is demonstrated based on characteristics of RCS. Combined with the hp-adaptive-Radau pseudo-spectral method and the receding horizon control algorithm under the optimal control model, the flight time and the threat probability of the UAV to the combat area were taken as the objective functions. An algorithm to adaptively adjust the weight coefficient of the performance index and switch the sub-objective function was used. The simulation results show that the proposed method can realize autonomous control of UAV attack trajectory under complex battlefield environment and multiple constraints. It can generate UAV flight path with little threat and short time and output relevant state and control parameters.