Intelligent model-based hierarchical fault diagnosis for satellite formations

Abstract

Formation flying is an emerging area in the Earth and space science and technology domain that utilize multiple inexpensive spacecraft by distributing the functionalities of a single platform among the miniature inexpensive platforms. Traditional spacecraft fault diagnosis and health monitoring practices that involve around-the-clock monitoring, threshold checking, and trend analysis of a large amount of telemetry data by human experts do not scale up well for multiple space platforms. In this paper a hierarchical fault detection and isolation (FDI) framework for spacecraft formation is proposed. Furthermore, fuzzy reasoning-based fault diagnosis for formation-level fault isolation related to attitude control is investigated. The proposed method has potential for acting as a mission enhancer by automating the fault diagnosis process for satellite formation flying missions.