{"title":"行星表面搬迁的自主制导和控制","authors":"Maurice Martin , Frederik Belien , Roger Förstner","doi":"10.1016/j.ifacsc.2024.100275","DOIUrl":null,"url":null,"abstract":"<div><p>Autonomous guidance and control (G&C) is vital for planetary surface exploration missions. The challenge of space applications is to find computational efficient algorithms that can be employed on-board while giving optimal and feasible solutions. Addressing this issue, this article presents a G&C solution for planetary surface relocations using thrust steering based on analytical suboptimal algorithms. The proposed solution is an alternative to on-board optimization using feedback linearization, time-optimal trajectories for each individual axis and a novel snap-based control, which considers the limits of the spacecraft design. The robustness of the G&C solution to model uncertainties is demonstrated using Monte Carlo simulations on the nonlinear surface dynamics of 67P/Churyumov–Gerasimenko (67P). Compared to other G&C approaches, the algorithms can easily be implemented on-board, reduce verification & validation costs, and minimize computational effort.</p></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"29 ","pages":"Article 100275"},"PeriodicalIF":1.8000,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Autonomous guidance and control for planetary surface relocations\",\"authors\":\"Maurice Martin , Frederik Belien , Roger Förstner\",\"doi\":\"10.1016/j.ifacsc.2024.100275\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Autonomous guidance and control (G&C) is vital for planetary surface exploration missions. The challenge of space applications is to find computational efficient algorithms that can be employed on-board while giving optimal and feasible solutions. Addressing this issue, this article presents a G&C solution for planetary surface relocations using thrust steering based on analytical suboptimal algorithms. The proposed solution is an alternative to on-board optimization using feedback linearization, time-optimal trajectories for each individual axis and a novel snap-based control, which considers the limits of the spacecraft design. The robustness of the G&C solution to model uncertainties is demonstrated using Monte Carlo simulations on the nonlinear surface dynamics of 67P/Churyumov–Gerasimenko (67P). Compared to other G&C approaches, the algorithms can easily be implemented on-board, reduce verification & validation costs, and minimize computational effort.</p></div>\",\"PeriodicalId\":29926,\"journal\":{\"name\":\"IFAC Journal of Systems and Control\",\"volume\":\"29 \",\"pages\":\"Article 100275\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2024-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IFAC Journal of Systems and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2468601824000361\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IFAC Journal of Systems and Control","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468601824000361","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Autonomous guidance and control for planetary surface relocations
Autonomous guidance and control (G&C) is vital for planetary surface exploration missions. The challenge of space applications is to find computational efficient algorithms that can be employed on-board while giving optimal and feasible solutions. Addressing this issue, this article presents a G&C solution for planetary surface relocations using thrust steering based on analytical suboptimal algorithms. The proposed solution is an alternative to on-board optimization using feedback linearization, time-optimal trajectories for each individual axis and a novel snap-based control, which considers the limits of the spacecraft design. The robustness of the G&C solution to model uncertainties is demonstrated using Monte Carlo simulations on the nonlinear surface dynamics of 67P/Churyumov–Gerasimenko (67P). Compared to other G&C approaches, the algorithms can easily be implemented on-board, reduce verification & validation costs, and minimize computational effort.