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Fuzzy physical programming for Space Manoeuvre Vehicles trajectory optimization based on hp-adaptive pseudospectral method

机译:基于HP-Adaptive Pseudtomectran方法的空间操纵车辆轨迹优化模糊物理规划

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摘要

In this paper, a fuzzy physical programming (FPP) method has been introduced for solving multi-objective Space Manoeuvre Vehicles (SMV) skip trajectory optimization problem based on hp-adaptive pseudospectral methods. The dynamic model of SMV is elaborated and then, by employing hp-adaptive pseudospectral methods, the problem has been transformed to nonlinear programming (NLP) problem. According to the mission requirements, the solutions were calculated for each single-objective scenario. To get a compromised solution for each target, the fuzzy physical programming (FPP) model is proposed. The preference function is established with considering the fuzzy factor of the system such that a proper compromised trajectory can be acquired. In addition, the NSGA-II is tested to obtain the Pareto-optimal solution set and verify the Pareto optimality of the FPP solution. Simulation results indicate that the proposed method is effective and feasible in terms of dealing with the multi-objective skip trajectory optimization for the SMV.
机译:本文介绍了一种基于HP-Adaptive Pseudtomect方法的多目标空间机动车辆(SMV)跳过轨迹优化问题的模糊物理编程(FPP)方法。 SMV的动态模型被阐述,然后通过采用HP-Adaptive伪谱方法,该问题已转变为非线性编程(NLP)问题。根据任务要求,针对每个单目标场景计算解决方案。为了获得每个目标的受损解决方案,提出了模糊物理编程(FPP)模型。通过考虑系统的模糊因子,建立偏好功能,使得可以获得适当的受损轨迹。此外,测试NSGA-II以获得静态最佳解决方案集并验证FPP解决方案的帕施加最优性。仿真结果表明,在处理SMV的多目标跳过轨迹优化方面,所提出的方法是有效和可行的。

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