Abstract:

The problem of PD-type Learning Observer (LO)-based fault reconstruction is addressed for satellite attitude control systems in this paper. By introducing differential term of measurement output estimation error into learning updating algorithm of the existing P-type LO, a novel PD-type LO is designed such that it can not only estimate satellite attitude angular velocities and attitude angles simultaneously, but also reconstruct actuator faults fast and accurately. Then, stability conditions of the proposed PD-type LO are explicitly provided, and a systematic PD-type LO design method is given based on linear matrix inequality technique. Further, the proposed PD-type LO design is extended for reconstructing attitude sensor faults in satellite. At last, the proposed approaches are applied to reconstruct thruster faults and gyroscope faults respectively in microsatellites, and simulation results validate the effectiveness of the proposed fault reconstruction approaches.

Key words: Satellite attitude control systems, Fault reconstruction, Learning observer, Linear matrix inequality