Solar-sail deep space trajectory optimization using successive convex programming

This paper presents a novel methodology for solving the time-optimal trajectory optimization problem for interplanetary solar-sail missions using successive convex programming. Based on the non-convex problem, different convexification technologies, such as change of variables, successive linearization, trust regions and virtual control, are discussed to convert the original problem into the formulation of successive convex programming. Because of the free final-time, successive linearization is performed iteratively for the nonconvex terminal state constraints. An augmented objective function is introduced to ensure the convergence performance and effectiveness of our algorithm. The original non-convex problem is transformed equivalently into a set of convex sub-problems, which can be solved effectively. Finally, numerical results demonstrate the effectiveness and accuracy of our algorithms.