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Target-enclosing affine formation control of two-layer networked spacecraft with collision avoidance

Target-enclosing affine formation control of two-layer networked spacecraft with collision avoidance

作     者:Yang XU Delin LUO Dongyu LI Yancheng YOU Haibin DUAN 

作者机构:School of Aerospace EngineeringXiamen UniversityXiamen 361005China Department of Control Science and EngineeringHarbin Institute of TechnologyHarbin 150001China State Key Laboratory of Virtual Reality Technology and SystemsSchool of Automation Science and Electrical EngineeringBeihang UniversityBeijing 100083China Department of Electrical&Computer EngineeringNational University of SingaporeSingapore 117583Singapore 

出 版 物:《Chinese Journal of Aeronautics》 (中国航空学报(英文版))

年 卷 期:2019年第32卷第12期

页      面:2679-2693页

核心收录:

学科分类:08[工学] 081105[工学-导航、制导与控制] 0811[工学-控制科学与工程] 

基  金:sponsored by National Natural Science Foundation of China (Nos. 61673327, 51606161, 11602209, 91441128) Natural Science Foundation of Fujian Province of China (No. 2016J06011) China Scholarship Council (No. 201606310153) 

主  题:Affine formation control Collision avoidance Lyapunov stability Target enclosing Two-layer strategy 

摘      要:This paper addresses a target-enclosing problem for multiple spacecraft systems by proposing a two-layer affine formation control strategy. Compared with the existing methods,the adopted two-layer network structure in this paper is generally directed, which is suitable for practical space missions. Firstly, distributed finite-time sliding-mode estimators and formation controllers in both layers are designed separately to improve the flexibility of the formation control system. By introducing the properties of affine transformation into formation control protocol design,the controllers can be used to track different time-varying target formation patterns. Besides, multilayer time-varying encirclements can be achieved with particular shapes to surround the moving target. In the sequel, by integrating adaptive neural networks and specialized artificial potential functions into backstepping controllers, the problems of uncertain Euler-Lagrange models, collision avoidance as well as formation reconfiguration are solved simultaneously. The stability of the proposed controllers is verified by the Lyapunov direct method. Finally, two simulation examples of triangle formation and more complex hexagon formation are presented to illustrate the feasibility of the theoretical results.

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