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Reliability-based trajectory optimization using nonintrusive polynomial chaos for Mars entry mission

机译:使用非侵入式多项式混沌进行火星进入任务的基于可靠性的轨迹优化

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摘要

This paper presents the reliability-based sequential optimization (RBSO) method to settle the trajectory optimization problem with parametric uncertainties in entry dynamics for Mars entry mission. First, the deterministic entry trajectory optimization model is reviewed, and then the reliability-based optimization model is formulated. In addition, the modified sequential optimization method, in which the nonintrusive polynomial chaos expansion (PCE) method and the most probable point (MPP) searching method are employed, is proposed to solve the reliability-based optimization problem efficiently. The nonintrusive PCE method contributes to the transformation between the stochastic optimization (SO) and the deterministic optimization (DO) and to the approximation of trajectory solution efficiently. The MPP method, which is used for assessing the reliability of constraints satisfaction only up to the necessary level, is employed to further improve the computational efficiency. The cycle including SO, reliability assessment and constraints update is repeated in the RBSO until the reliability requirements of constraints satisfaction are satisfied. Finally, the RBSO is compared with the traditional DO and the traditional sequential optimization based on Monte Carlo (MC) simulation in a specific Mars entry mission to demonstrate the effectiveness and the efficiency of the proposed method.
机译:本文提出了一种基于可靠性的顺序优化(RBSO)方法,解决了火星进入任务中动力学参数不确定的轨迹优化问题。首先,回顾了确定性的进入轨迹优化模型,然后建立了基于可靠性的优化模型。此外,提出了一种改进的顺序优化方法,其中采用了非侵入式多项式混沌扩展(PCE)方法和最可能点(MPP)搜索方法,以有效解决基于可靠性的优化问题。非侵入式PCE方法有助于随机优化(SO)和确定性优化(DO)之间的转换,并有助于有效地逼近轨迹解。 MPP方法用于评估约束满足的可靠性,仅达到必要的水平,从而进一步提高了计算效率。在RBSO中重复进行包括SO,可靠性评估和约束更新的循环,直到满足约束满足的可靠性要求。最后,在特定的火星进入任务中将RBSO与传统的DO和基于蒙特卡洛(MC)仿真的传统顺序优化进行了比较,以证明该方法的有效性和效率。

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