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本文引用格式:刘博,王云财,张松涛,韩柠.火星探测器制动捕获多目标优化策略[J].动力学与控制学报,2019,17(4):356~361;   Liu Bo,Wang Yuncai,Zhang Songtao,Han Ning.Multi-objective optimization strategy for brake capture of mars explorer[J].Journal of Dynamics and Control,2019,17(4):356-361.
火星探测器制动捕获多目标优化策略    点此下载全文
刘博  王云财  张松涛  韩柠
国防科技大学 空天科学学院, 长沙 410073,北京控制与电子技术研究所, 北京 100038,北京控制与电子技术研究所, 北京 100038,北京控制与电子技术研究所, 北京 100038
基金项目:国家自然科学基金资助项目(60904009)
DOI:10.6052/1672-6553-2019-032
摘要:
      本文提出了一种基于动态加权算法的火星探测器制动捕获多目标优化策略,该策略在火星探测器制动捕获过程中同时考虑制动目标轨道精度和燃料消耗,相对于传统的捕获策略,具有同等运算量下更易收敛到最优解的优势.本文以制动推力方向沿火星探测器速度反向的制动捕获方法为例,首先,描述了有限推力下火星探测器的制动捕获问题,然后,针对优化模型的非线性动态耦合特性,研究了基于自适应参数调整的动态PSO算法,最后,应用动态PSO算法和动态加权算法,设计了火星探测器制动捕获多目标优化策略.仿真分析表明,相比于传统的单目标优化策略,本文设计的火星探测器制动捕获多目标优化策略,不仅能够满足精度要求,而且更容易得到燃料相对最优值,减少燃料消耗.因此具有一定的研究和应用价值.
关键词:多目标优化,动态加权,自适应,粒子群,火星探测,制动捕获
Multi-objective optimization strategy for brake capture of mars explorer    Download Fulltext
Liu Bo  Wang Yuncai  Zhang Songtao  Han Ning
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Abstract:
      A multi objective optimization strategy based dynamic weighting algorithm is proposed in this paper for the optimal brake capture accomplished by a mars explorer to achieve the targeted parking orbit with minimal fuel consumption. Comparing with the conventional single objective optimization strategy, a key advantage of the developed multi objective optimization formulation is that it considers the fuel consumption as well as the targeting accuracy simultaneously to achieve the optimization likely. The dynamical model of mars explorer is established where the direction of finite thrust is contrary to its velocity. Then, focusing on the improvement of particle swarm optimization (PSO) performance, adaptive PSO technique with dynamically adjusting parameters is presented to address the particular challenges posed by the optimization design of complex dynamic system with highly nonlinear coupling. What’s more, the dynamic weighting strategy along with the adaptive PSO is applied on the multi objective optimization between fuel consumption and targeting accuracy. The multi objective optimization strategy demonstrates a higher probability of seeking less fuel consumption than comparable conventional single objective optimization strategy when the targeting accuracy is in conformity with the requirement. Thus it has remarkable application value in actual projects.
Keywords:multi objective optimization,dynamic weighting,adaptive control,particle swarm optimization (PSO),brake capture, mars exploration
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