Fast trajectory replanning for cooperative vehicles using sequential convex programming

With the rapid changes of the flight environment and situation, there will be various unexpected situations while multiple missiles are performing the missions. To fast cope with the various situations in mission executions, the conventional sequential convex programming algorithm and the parallel-based sequential convex programming algorithm for multiple missiles fast trajectory replanning are proposed in this paper. The originally non-convex trajectory optimization problem is reformulated into a series of convex optimization subproblems based on the sequential convex programming method. The conventional sequential convex programming algorithm is developed through linearization, successive convexification, and relaxation techniques to solve the convex optimization subproblems iteratively. However, multiple missiles are related through various cooperative constraints. When the trajectory optimization of multiple missiles is formulated as an optimal control problem to solve, the complexity of the problem will increase dramatically as the number of missiles increases. To alleviate the coupled effect caused by multiple aerodynamically controlled missiles, the parallel-based sequential convex programming algorithm is proposed to solve the trajectory optimization problem for multiple missiles in parallel, reducing the complexity of the trajectory optimization problem and significantly shortening the computation time. Numerical simulations are provided to verify the convergence and effectiveness of the conventional sequential convex programming algorithm and the parallel-based sequential convex programming algorithm to cope with the trajectory optimization problem with various constraints. Furthermore, the optimality and the real-time performance of the proposed algorithms are discussed in comparative simulation examples.