Mcrls for On-line Spacecraft Mass- and Thruster-property Identification

This paper will present recent advances in algorithms developed to achieve accurate on-line ID. These algorithms use and reference the MCRLS ID algorithm [1]. Initial mass-property ID algorithms as developed for the X-38 v.201 spacecraft and Mini-AERCam [2] are updated and extended here. Experimental results validating a subset of these algorithms on the MIT SPHERES spacecraft in zero-g aircraft flight tests are presented in [3]. For brevity, the reader is referenced to those publications for supporting material. The abovementioned spacecraft and the NASA Ames air-bearing simulator are shown below. Spacecraft control, state estimation, and faultdetection-and-isolation systems are affected by unknown variations in the vehicle mass and thruster properties. It is often difficult to accurately measure inertia terms on the ground, and mass properties can change on-orbit as fuel is expended, the configuration changes, or payloads are added or removed. Multiple concurrent recursive least squares identification (MCRLS ID) algorithms using gyros and accelerometers to monitor vehicle motions are used here to identify on-line, vehicle inertia, inverseinertia, center of mass, thruster force, and total mass. Originally developed for application to the X-38 v.201 spacecraft, the algorithms have been extended and implemented on the MIT SPHERES experimental spacecraft, which are now awaiting launch to the ISS for space-based testing. The MCRLS ID algorithm is summarized briefly, and advances in the specific ID algorithms are presented. An accurate and efficient filtering method for estimating angular acceleration from raw gyro signals is presented. GPS Antenna