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Probability Distribution Evolution Algorithm to Inertial Parameters Identification for Space Target
Feng GH; Li WH(李文皓); Zhang H(张珩); Xiao XX(肖歆昕); Zhang J(章杰)
会议录名称2017 4TH INTERNATIONAL CONFERENCE ON SYSTEMS AND INFORMATICS (ICSAI)
2017
会议名称4th International Conference on Systems and Informatics (ICSAI)
会议日期NOV 11-13, 2017
会议地点Hangzhou, PEOPLES R CHINA
摘要

A new probability distribution evolution algorithm (PDE) is proposed for inertial parameters identification of space target. Based on the conservation of angular momentum, the number of space target's inertial unknown parameters is reduced from 10 to 4 by using pseudo inverse operation. The pseudo-inverse solution consistency in multiple groups status is proposed as the optimization evaluation index, and identification simulations are carried out using PDE. A evaluation strategy is given to significantly improve identification accuracy while a small increase of calculation consumption. The statistical results of identification simulation examples show that by only using angular momentum measurement data, the proposed PDE and strategy can achieve the high precision identification for the target inertial parameters with large range change. And PDE is equivalent to the optimization ability of typical evolutionary algorithms, such as genetic algorithm (GE) and differential evolution algorithm (DE).

关键词Probability Distribution Evolution Algorithm (Pde) Inertial Parameters Identification Space Target Pseudo-inverse Solution Consistency
WOS记录号WOS:000427752100010
资助信息This research was supported by the National Natural Science Foundation of China [grant number 11702294, 11002143] ; and the Key Project of Chinese National Programs for Fundamental Research and Development, 973 program [grant number 2013CB733000].
ISBN号978-1-5386-1107-4
收录类别EI
语种英语
引用统计
文献类型会议论文
条目标识符http://dspace.imech.ac.cn/handle/311007/75551
专题先进制造工艺力学重点实验室
通讯作者Li WH(李文皓)
推荐引用方式
GB/T 7714
Feng GH,Li WH,Zhang H,et al. Probability Distribution Evolution Algorithm to Inertial Parameters Identification for Space Target[C],2017.
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