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对于跳跃式再入轨迹优化问题,通常的求解方法是不经任何分析直接约束动压、过载和热流密度,再加上控制变量滚转角的约束,往往使问题变得复杂而难以求解。基于跳跃式再入轨迹的动力学特性,将轨迹进行分段,并逐段分析路径约束的特点和内在联系,建立起它们之间的解析关系式,由此得到跳跃式再入轨迹优化问题中路径约束的串行施加策略。运用该策略可以在某些情况下减少路径约束的个数,降低优化问题的复杂度;选择优化方法时,为了兼顾全局最优性与高精度结果,采用基于粒子群优化(PSO)算法和高斯伪谱法(GPM)的两层优化策略。仿真结果表明,采用两层优化策略可以得到满足约束的高精度解,路径约束串行施加策略正确可行,优化计算结果与理论分析结论一致。
For the jump re-entry trajectory optimization problem, the usual solution is to directly restrain the dynamic pressure, overload and heat flux without any analysis, and the constraints of the control variable roll angle often make the problem complicated and difficult to solve. Based on the dynamic characteristics of the leapfrog reentry trajectory, the trajectory is segmented, and the characteristics and the internal relations of the trajectory restraint are analyzed section by section, and the analytic relation between them is established, so as to obtain the jump reentry trajectory optimization problem The Path Constraint Serial Application Strategy. This method can reduce the number of path constraints in some cases and reduce the complexity of the optimization problem. In order to balance global optimality with high accuracy, the PSO algorithm and Gaussian Pseudospectral method (GPM) two-tier optimization strategy. The simulation results show that the two-level optimization strategy can get the high-precision solution that satisfies the constraint, and the path-constrained serial application strategy is correct and feasible. The optimization calculation results are in good agreement with the theoretical analysis.