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Maximum-Normal-Load Entry Trajectory Optimization for Hypersonic Glide Vehicles

机译:高超声速滑行飞行器的最大法向载荷进入轨迹优化

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Finding the optimal entry trajectory with maximum peak normal load is important to assess the maneuverability of hypersonic glide vehicles for mission flexibility and large footprint generations. This paper investigates the utilization of mixed-integer programming methods for solving the problem of maximum-normal-load entry trajectory optimization under the heat rate and dynamic pressure constraints. The maximum-normal-load entry problem is formulated as a nonconvex discrete-event optimal control problem subject to various state and control constraints, path constraints, and terminal constraints. A Big-M method is used to relax the problem into a mixed-integer nonlinear programming problem, which is proved to be equivalent to the original MaxMax problem. Through successive convex approximations of the nonlinear dynamics and nonconvex path constraints, a sequential mixed-integer convex programming method is developed to find the solution. There are efficient mixed-integer convex programming solvers that can solve each relaxed subproblem with a global optimum if the feasible set of the subproblem is nonempty. The convergence of the proposed methodology is demonstrated by numerical simulations.
机译:寻找具有最大峰值法向载荷的最佳进入轨迹对于评估高超音速滑行飞行器的机动性和任务灵活性和产生大量足迹非常重要。本文研究了混合整数规划方法在热率和动压力约束下解决最大法向载荷进入轨迹优化问题的方法。最大法向负荷进入问题被公式化为非凸离散事件最优控制问题,该问题受各种状态和控制约束,路径约束和终端约束的约束。使用Big-M方法将问题放松为混合整数非线性规划问题,事实证明该问题与原始MaxMax问题等效。通过非线性动力学和非凸路径约束的连续凸逼近,开发了一种顺序混合整数凸规划方法来找到解决方案。如果子问题的可行集为非空,则存在有效的混合整数凸规划求解器,该求解器可以全局最优地求解每个松弛子问题。数值仿真证明了所提出方法的收敛性。

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