全球定位系统2026，Vol.51Issue(2)：30-39,10.DOI:10.12265/j.gnss.2026028
基于故障后主被动结合策略的深空探测控制自主重构方法
Autonomous reconfiguration method for deep space exploration control based on the active-passive combined strategy after actuator failure
摘要
Abstract
Unmanned vehicles engaged in deep-space exploration missions typically lack ground support and on-orbit maintenance capabilities.As a result,the actuators in their control systems operate frequently,making faults inevitable.To restore the prescribed functions of the control system after actuator faults,this paper proposes an autonomous reconfiguration method based on a hybrid passive-active strategy.First,actuator degradation-induced system faults are uniformly characterized using residual effectiveness factors.An optimal reconfiguration cost matrix,which depends on the fault-related system parameters,is introduced as a performance indicator to determine and partition the reconfigurable fault set.Second,the applicability of control laws constructed from the optimal reconfiguration cost matrix under different fault conditions is analyzed,and a dedicated control law is assigned to each reconfigurable fault subset.Finally,a control law selection and switching mechanism based on real-time fault information is designed to achieve fault-specific autonomous reconfiguration.The proposed method addresses multiple fault scenarios using a finite number of control laws and does not require online controller synthesis.Simulation results demonstrate that the proposed approach can fully exploit the residual effectiveness of faulty actuators and achieve the reconfiguration objective with a relatively low reconfiguration cost.关键词
容错控制/执行器故障/Gramian矩阵/系统重构/闭环稳定性Key words
fault-tolerant control/actuator fault/Gramian matrix/system reconfiguration/closed-loop stability分类
航空航天引用本文复制引用
刘凯,符方舟,董天舒,屠园园..基于故障后主被动结合策略的深空探测控制自主重构方法[J].全球定位系统,2026,51(2):30-39,10.基金项目
国家自然科学基金(U22B6001,62388101,62403047,62473389) （U22B6001,62388101,62403047,62473389）
广东省自然科学基金(2025B1515020097,2024A1515011730) （2025B1515020097,2024A1515011730）
