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

作　　者：Zhixiong Ji Gefei Shi 

机构地区：[1]School of Aeronautics and Astronautics,Sun Yat-sen University,Guangzhou 510275,China [2]Shenzhen Campus of Sun Yat-sen University,Shenzhen 518107,China [3]Shenzhen Key Laboratory of Intelligent Microsatellite Constellation,Shenzhen 518107,China

出　　处：《Astrodynamics》2024年第2期261-269,共9页航天动力学（英文）

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)。

摘　　要：This study proposes a novel adaptive neural dynamic-based hybrid control strategy for stable subsatellite retrieval of two-body tethered satellite systems.The retrieval speed is given analytically,ensuring a libration-free steady state.To 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 subsatellite.To 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 controller.The Lyapunov stability of the control strategy is demonstrated analytically.Numerical simulations validate the proposed control strategy,demonstrating well-allocated control inputs for both controllers and good control performance.

关 键 词：tethered satellite system(TSS) stable retrieval hybrid control adaptive neural-dynamic (AND)control fuzzy control 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]