Adaptive neural dynamic-based hybrid control strategy for stable retrieval of tethered satellite systems

作     者：Zhixiong Ji Gefei Shi 

作者机构：School of Aeronautics and AstronauticsSun Yat-sen UniversityGuangzhou 510275China Shenzhen Campus of Sun Yat-sen UniversityShenzhen 518107China Shenzhen Key Laboratory of Intelligent Microsatellite ConstellationShenzhen 518107China 

出 版 物：《Astrodynamics》 (航天动力学（英文）)

年 卷 期：2024年第8卷第2期

页      面：261-269页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：funded by the National Natural Science Foundation of China(Grant No.12102487) Guangdong Basic and Applied Basic Research Foundation(Grant No.2023A1515012339) Shenzhen Science and Technology Program(Grant No.ZDSYS20210623091808026) 

主　　题：tethered satellite system(TSS) stable retrieval hybrid control adaptive neural-dynamic (AND)control fuzzy control 

摘      要：This study proposes a novel adaptive neural dynamic-based hybrid control strategy for stable subsatellite retrieval of two-body tethered satellite *** retrieval speed is given analytically,ensuring a libration-free steady *** mitigate the potential libration motion,a general control input signal is generated by an adaptive neural-dynamic(AND)algorithm and executed by adjusting the retrieval speed and thruster on the *** address the limited retrieval speed and improve the control performance,the thruster controller is manipulated according to a novel advanced state fuzzy control law based on higher-order libration states,whereas the remaining control input is allocated to the speed *** Lyapunov stability of the control strategy is demonstrated *** simulations validate the proposed control strategy,demonstrating well-allocated control inputs for both controllers and good control performance.