Reentry Trajectory Optimization for Hypersonic Glide Vehicle with Flexible Initial Conditions

In the reentry trajectory optimization for unpowered hypersonic glide vehicles (HGVs), the initial reentry conditions (IRCs), which are crucial for flight performance, are partly flexible instead of being specified. Aiming at simultaneously determining the optimal IRCs and optimal control policy, a hybrid optimization strategy with an evaluate-during-optimize framework is proposed in this paper. The IRCs are considered as additional independent design variables, and an evaluation process with multiple performance indicators is established to determine the best IRCs. With the analytic hierarchy process (AHP)-based multicriteria decision-making (MCDM) method, a synthesized scalar objective function is set up. Adopting this objective function, feedback information from the evaluation process can be fully included in the optimization process, resulting in a unified optimization framework. The Chebyshev pseudospectral method (CPM) is then introduced as a direct method for solving the resulting trajectory optimization problem. Numerical simulation results for a generic HGV show that the proposed technique is efficient and straightforward. Moreover, this strategy has strong universality for solving optimal control problems with flexible initial conditions.