Multi-objective optimization on the shock absorber design for the lunar probe using nondominated sorting genetic algorithm II. (14th July 2017)

• Record Type: Journal Article
• Authors: Liu, Yuanyuan; Song, Shunguang; Wang, Chunjie
• Is Part Of: International journal of advanced robotic systems. Volume 14:Number 4(2017:Jul./Aug.)
• Publication Date: 2017-07-14
• Subjects: Lunar probe -- soft-landing stability -- honeycomb shock absorber -- multi-objective optimization -- NSGA-II; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.1177/1729881417720467
• Languages: English
• ISSNs: 1729-8806

Abstract

In this article, the design on the shock absorber of the lunar probe soft landing can be considered as a single- or multi-objective optimization problem. Here, the optimized objective parameters include the maximum toppling stability, defined as D min, and the minimum stroke of primary strut energy absorption, SP max . However, the two optimized variables are conflict objectives. In order to give an overall consideration about the multi-performances of landing, the multi-objective optimization strategy is proposed and nondominated sorting genetic algorithm II is employed to find the best decision parameters of the shock absorber design. To conduct the optimizations, firstly, the worst landing cases and safety boundaries for both toppling and primary strut energy absorptions are obtained by the computer simulation experiments. Both single- and multi-objective optimizations are then implemented aiming to expand the stability boundary. The results show that the landing stability is effectively improved after optimizations, and also demonstrate that the multi-objective optimization strategy is superior to that of the single-objective optimization.