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针对大角度机动情况下带挠性附件航天器转动惯量在轨辨识的问题,提出一种将转动惯量参数估计和挠性附件状态估计相结合的并发递推算法。该算法以大角度机动情况下带挠性附件航天器的非线性动力学模型为基础,分别利用广义卡尔曼滤波做挠性附件振动模态的状态估计,最小二乘法做转动惯量的参数估计。最后通过并发递推算法将二者结合,完成了带挠性附件航天器的转动惯量参数辨识。为了提高算法的效率,采用一步最小二乘、多步广义卡尔曼滤波并发递推的算法。仿真结果表明,该辨识方法兼具高精度、高效率,并且算法有一定的抗干扰能力。
Aiming at the problem of on-orbit identification of moment of inertia of a spacecraft with flexible attachments under large-angle maneuver, a concurrent recursive algorithm is proposed, which combines the estimation of moment of inertia parameters and the state estimation of flexible attachments. Based on the nonlinear dynamics model of the spacecraft with flexible attachments under high-angle maneuver, the proposed method uses the generalized Kalman filter to estimate the vibration modes of the flexible attachments and the least square method to estimate the moment of inertia. Finally, the two algorithms are combined by recursion recursion algorithm, and the inertia parameter identification of the spacecraft with flexible attachment is completed. In order to improve the efficiency of the algorithm, one-step least squares, multi-step generalized Kalman filter concurrent recursive algorithm. Simulation results show that this method has both high precision and high efficiency, and the algorithm has some anti-interference ability.