A method for on-orbit identification of moment of inertia of spacecraft with flexible attachments under large-angle maneuvering

Abstract

The invention discloses a method for in-orbit identification of moment-of-inertia of spacecraft with flexible attachment in a large angle maneuver, and the method comprises the following steps: S1) according to the altitude dynamic equation of the spacecraft and the motion equation of the flexible attachment, establishing a nonlinear system dynamic model; S2) using the angular velocity data collected by a gyroscope and the control moment data of the spacecraft maneuvering and utilizing the generalized Kalman filter algorithm to estimate the vibration mode of the flexible attachment and its derivatives; S3) writing the attitude dynamic equation of the satellite with the flexible attachment in the form of least squares; using the second derivative (described in the abstract) of vibration mode estimated in S2 and using the least squares algorithm to identify the moment-of-inertia of the satellite; and S4) mutually calling the vibration mode estimated from the generalized Kalman filter algorithm in S2 and the moment-of-inertia identified from the lease squares in S3; repeating S2 and S3 steps; and through the combination and the recursion of the generalized Kalman filter and least squares method, obtaining the identification value for the moment-of-inertia.

Description

technical field [0001] The invention relates to an on-orbit identification method for the moment of inertia of a spacecraft with a flexible attachment under large-angle maneuvering. Background technique [0002] The traditional method is to do the identification of the moment of inertia of the spacecraft with a flexible attachment, and the parameter to be identified is used as the state quantity, and the method is extended to the state equation. However, the extended Kalman filter is used in parameter estimation, because it does not take into account the influence of parameter changes on the gain, which can easily lead to biased estimation or divergence. The method of the invention utilizes the generalized Kalman filter to estimate the state quantity of the vibration mode, and then uses the least square method to estimate the parameters, and the cycle is endless until the result converges. [0003] The traditional method directly uses the extended Kalman filter for paramete...

AI Technical Summary

Problems solved by technology

[0004] The traditional method has better accuracy in calculating the principal inertia, but the accuracy in calculating the product of inertia is poor

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