Improved gradient-based algorithm for solving aeroassisted vehicle trajectory optimization problems

A tudyt proposes a two-step interior-point sequential quadratic programming (IPSQP) approach which combines the advantages of SQP and IP. A special feature of the proposed method is that the user can control the iteration of the inner loop so that theQPsubproblem does not need to be exactly solved. By using the iterate solution calculated from the inner loop, it becomes more accurate to identify the active set, which will have positive influences in generating the Lagrangian multipliers and next iteration points. Compared with standard SQP, it tends to be more stable and can reduce the computational time.