Online Trajectory Planning of Morphing Vehicle Based on Sequential Convex Programming

Compared to traditional fixed wing aircraft, morphing vehicle can choose the best performance shape based on different mission requirements and flight conditions with morphing mechanisms. Therefore, the demand for trajectory planning for morphing vehicle is becoming increasingly strong. In this paper, a trajectory planning algorithm based on sequence convex programming with compensation factors is proposed to address the high nonlinearity of the aerodynamic model, the large computational load, and the difficulty in convergence during the trajectory planning process of morphing vehicle. Firstly, the rate of attack angle, the rate of back angle, and the rate of sweep angle are introduced as new control variables to decouple the original motion equation and smooth the angle state variables. Then, compensation factors are added to the motion equation and terminal constraints during the convexification process, and a penalty function with compensation factors is added to the objective function. The planning problem is then transformed into a convex optimization problem, which is solved using a sequential convex programming algorithm to achieve the goal of solving the strong nonlinearity caused by morphing, the difficult convergence problem caused by discretization, and the final convergence accuracy. Finally, the design method is compared and verified with the simulation results based on the pseudospectral trajectory planning algorithm. The simulation results show that compared with the pseudospectral method, the proposed algorithm can achieve fast online trajectory planning of morphing vehicle, with a reduction in computational time to 1/6 and high solution accuracy, resulting in higher overall efficiency.