Online Reentry Trajectory Optimization Using Modified Sequential Convex Programming for Hypersonic Vehicle

In this article, a highly nonlinear trajectory optimization problem for reentry vehicles is rapidly solved by the proposed modified sequential convex programming (MSCP) method. A logarithm linearization approach is proposed to decouple the dynamics of high order and nonconvex path constraints of heat rate, dynamic pressure, and normal load. Next, the model including the no-fly zone constraint, and the nonconvex objective function are convexified with first-order Taylor series expansion. Subsequently, the continuous-time optimal problem is converted to an equivalent finite-dimensional sequential convex programming (SCP) problem. Moreover, a compensation term is added to the state equations to maintain the feasibility of the reformulated problem. Consequently, to guarantee the optimality of the solution, a penalty term with respect to the compensation term is added to the objective function. In the end, an online optimization scheme with MSCP is proposed. Compared to a general proposed optimal control solver, numerical simulations are conducted to verify the optimality and fast convergence of MSCP. Furthermore, online optimization simulations demonstrate the validity of the proposed online scheme for pop-up no-fly zone and mission temporary changes.