The attitude motion of a satellite in space can be simulated on the ground by three-axis air bearing table, which is a ground-based intelligent unmanned system. This paper aims at the problem of low identification accuracy when the quality characteristic parameters of the three-axis air bearing table are identified by the general recursive least square method (RLS) or Kalman filter algorithm (KF). A method is designed to filter the angular velocity with random noise using the tracking differentiator (TD filter), and then use RLS and KF to identify the quality characteristics of the air bearing table. Finally, the two proposed identification methods, TD-RLS and TD-KF, are simulated and analyzed. The simulation results show that the identification accuracy of various parameters is greatly improved after the angular velocity is filtered by the TD filter. Among them, the quality characteristic estimation based on the TD-RLS identification method has the highest identification accuracy. The estimation error of the main moment of inertia is better than 1.2%, the estimation error of the inertia product is better than 7.6% the interference torque estimation error is better than 5.2%.
Research on Automatic Identification of Quality Characteristic Parameters of Three-Axis Air Bearing Table
Lect. Notes Electrical Eng.
International Conference on Autonomous Unmanned Systems ; 2021 ; Changsha, China September 24, 2021 - September 26, 2021
Proceedings of 2021 International Conference on Autonomous Unmanned Systems (ICAUS 2021) ; Chapter : 6 ; 54-62
2022-03-18
9 pages
Article/Chapter (Book)
Electronic Resource
English
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