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On-Line, Gyro-Based, Mass-Property Identification for Thruster-Controlled Spacecraft Using Recursive Least Squares

机译:基于递归最小二乘法的推进器控制航天器的在线,基于陀螺的质量特性识别

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Spacecraft control, state estimation, and fault-detection-and-isolation systems are affected by unknown v aerations in the vehicle mass 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. Recursive least squares -based algorithms that use gyro signals to identify the center of mass and inverse inertia matrix are presented. They are applied in simulation to 3 thruster-controlled vehicles: the X-38 and Mini-AERCam under development at NASA-JSC, and the SAM, an air-bearing spacecraft simulator at the NASA-Ames Smart Systems Research Lab (SSRL).

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