空间机器人惯性参数辨识的粒子群优化新算法 | |
Alternative Title | A New Particle Swarm Optimization Approach to the Inertia Parameters Identification of Onorbit Space Robot |
马欢; 李文皓![]() ![]() | |
Source Publication | 宇航学报
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2015 | |
Volume | 36Issue:3Pages:278-283 |
ISSN | 1000-1328 |
Abstract | 提出了针对一类多自由度空间机器人卫星惯性参数在轨辨识的一种粒子群(PSO)优化新算法。通过粒子邻域限定的多样性保持、低效粒子随机重置和粒子误差的序列性评价,得到了比常规方法更好的结果,且具有无附加燃料消耗、线动量测量和特定的机器人路径规划等便利性优点。仿真算例表明,该改进方法具有较高的准确性与效率。 |
Other Abstract | A new kind of particle swarm optimization (PSO) algorithm is proposed to identify the inertia parameters of an onorbit satellite equipped with a class of MultiDOF robot. By diversity maintenance by limiting the definition of particle neighborhood, random reset of inefficient particles and sequential evaluation of particle errors, a better result is achieved in contrast with the classical PSO algorithm. Moreover, it doesn’t require additional fuel consumption, linear momentum measurement nor specific robot path planning. The simulation experiments show that the improved algorithm performs more accurately and efficiently. |
Keyword | 空间机器人 参数辨识 粒子群算法 卫星 |
DOI | 10.3873/j.issn.1000-1328.2015.03.005 |
URL | 查看原文 |
Indexed By | EI ; CSCD |
Language | 中文 |
CSCD ID | CSCD:5375875 |
Department | MAM遥科学技术 |
Citation statistics |
Cited Times:5[CSCD]
[CSCD Record]
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Document Type | 期刊论文 |
Identifier | http://dspace.imech.ac.cn/handle/311007/56631 |
Collection | 先进制造工艺力学实验室 |
Corresponding Author | 肖歆昕 |
Recommended Citation GB/T 7714 | 马欢,李文皓,肖歆昕. 空间机器人惯性参数辨识的粒子群优化新算法[J]. 宇航学报,2015,36,3,:278-283. |
APA | 马欢,李文皓,&肖歆昕.(2015).空间机器人惯性参数辨识的粒子群优化新算法.宇航学报,36(3),278-283. |
MLA | 马欢,et al."空间机器人惯性参数辨识的粒子群优化新算法".宇航学报 36.3(2015):278-283. |
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