Augmented Kalman filter based satellite interference torque estimation method

Abstract

The invention discloses an augmented Kalman filter based satellite interference torque estimation method. The method includes steps: S1, extracting steady-state satellite flywheel rotating speed in anorbital period and satellite inertia angular speed measured by a gyroscope from satellite in-orbit data, converting the flywheel rotating speed into flywheel angular momentum, and subjecting the flywheel angular momentum to numerical difference calculation to obtain an approximate value of a flywheel output torque; S2, taking the approximate value of the flywheel output torque and the satellite inertia angular speed measured by the gyroscope as input of a Kalman filter, taking a satellite in-orbit environmental interference torque as a state quantity, and establishing a state updating equation and a measurement equation of an augmented system to obtain a Kalman filter algorithm of the environmental interference torque; S3, subjecting the augmented system to Kalman filter to obtain an estimated value of the environmental interference torque, and adding the estimated value of the environmental interference torque as a feed-forward signal of a satellite control system into a satellite attitude controller.

Description

technical field [0001] The invention relates to an optimal estimation technology of external interference moment received by satellites, in particular to a method for estimating satellite interference moment based on augmented Kalman filtering. Background technique [0002] Kalman filtering is one of the most commonly used algorithms in information fusion algorithms, and it is mainly used for real-time fusion of dynamic multi-sensor redundant data. The main point is to correct the uncertainty of the model by means of measurement, overcome the discreteness of measurement with the continuity of the model, and suppress the uncertainty of the model with the certainty of measurement. When the state equation and the measurement equation of the system are both linear and the system noise and sensor measurement noise are both Gaussian white noise, the application of the classical Kalman filter algorithm can provide the only statistically optimal estimate for the fused data. After t...

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Problems solved by technology

[0004] New space missions put forward higher requirements on the control accuracy of satellites. However, due to the influence of large-scale low-frequency flexible accessories on the current star, as well as the performance limitations of attitude measurement sensors and attitude control actuators, the bandwidth of satellite attitude controllers cannot be too large. High, which in turn restricts the anti-interference ability of the system

Since the ground cannot accurately model the external disturbance torque on the satellite, if only the disturbance torque model established on the ground is used to apply the feedforward signal to the controller, the accurate compensation for the disturbance cannot be realized, so the feedforward information has a great impact on the control accuracy. The improvement is not ideal

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