ESA GNC Conference Papers Repository
Spacecraft Parameter Identification using S-estimators
This paper focus on the simultaneous robust identification of spacecraft inertia and center of mass using the least squares algorithm and S-estimator techniques. A multiple concurrent recursive least squares (MCRLS) approach was implemented and tested using a simulator of the AVUM, the last stage of the VEGA launch system. Also, a new algorithm to compute regression S-estimates was applied to the spacecraft inertia and center of mass identification problem. This new algorithm, based on the fast-S formulation, seeks to ally high robustness to outliers with the recursive features of the standard RLS. It is aimed at realtime usage in a parameter identification setting. The performance of the MCRLS method was compared with an augmented version of the same approach implementing the new S-estimation algorithm, the multiple concurrent S-estimator (MCS). The MCS performed at the same level of the MCRLS in the absence of outliers. Considering polluted data sets, the augmented version performed far better. A simple fault detection and isolation algorithm for thruster malfunction was developed and tested. It was able to identify successfully the occurrence of thruster misfire event and which thrusters failed to fire.