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Constrained reentry trajectory optimization based on improved particle swarm optimization algorithm

机译:基于改进粒子群优化算法的受限再入轨迹优化

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This paper proposes an improved particle swarm optimization (PSO) using "step-phase" adjustment strategy for inertia weight to generate the minimum time reentry trajectory for hypersonic reentry vehicles based on the parameterized bank angle profile. According to engineering experience, the velocity-dependent bank angle profile is developed using the "two-flip strategy", thereby reducing the dimensionality of particles. The reentry constraints are processed by penalty function. Especially, the no-fly zone (NFZ) constraint is enforced by extreme method that setting penalty weight to be an extremely large positive number on the condition that the trajectory passes through the NFZ . Simulation results illustrate that the improved PSO algorithm based on the parameterized bank angle profile proves to be capable to generate a complete and optimal three degrees of freedom (3-DOF) reentry trajectory rapidly.
机译:本文采用了使用惯性重量的“步进阶段”调节策略的改进的粒子群优化(PSO),以产生基于参数化的银行角度分布的高回复速度的最小时间再入轨迹。 根据工程经验,使用“双翻转策略”开发速度依赖性银行角度曲线,从而降低粒子的维度。 再入限制由惩罚函数处理。 特别是,通过极端方法强制执行No-Fly区(NFZ)约束,使得在轨迹通过NFZ的条件下将罚批设置为极大的正数。 仿真结果表明,基于参数化的银行角度配置文件的改进的PSO算法证明能够快速地产生完整和最佳的三个自由(3-DOF)再入轨迹。

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