| On extended state Kalman filter-based identification algorithm for aerodynamic parameters |
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| 引用本文： | Wenyan Bai,Ruizhe Ji,Peng Yu,Wenchao Xue. On extended state Kalman filter-based identification algorithm for aerodynamic parameters[J]. 控制理论与应用(英文版), 2024, 22(2): 235-243 |
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| 作者姓名： | Wenyan Bai Ruizhe Ji Peng Yu Wenchao Xue |
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| 作者单位： | 1 Beijing Aerospace Automatic Control Institute, Beijing 100854, China;2 School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China3 Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing 100083, China;4 Key Laboratory of Systems and Control, Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China |
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| 基金项目： | This work was supported by the National Natural Science Foundation of China (No. 62122083) and Youth Innovation Promotion Association, CAS. |
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| 摘 要： | In this paper, the problem of time-varying aerodynamic parameters identification under measurement noises is studied. Byanalyzing the key aerodynamic parameters that affect the aircraft control system, a system model with extended states foridentifying equivalent aerodynamic parameters is established, and error parameters are extended to the system state, avoidingthe difficulty caused by the unknown dynamic in the system. Furthermore, an identification algorithm based on extended stateKalman filter is designed, and it is proved that the algorithm has quasi-consistency, thus, the estimation error can be evaluatedin real time. Finally, the simulation results under typical flight scenarios show that the designed algorithm can accuratelyidentify aerodynamic parameters, and has desired convergence speed and convergence precision.
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| 关 键 词： | Aerodynamic parameters · Parameter identification · Extended state Kalman filter |
On extended state Kalman filter-based identification algorithm for aerodynamic parameters |
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| Wenyan Bai,Ruizhe Ji,Peng Yu,Wenchao Xue. On extended state Kalman filter-based identification algorithm for aerodynamic parameters[J]. Journal of Control Theory and Applications, 2024, 22(2): 235-243 |
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| Authors: | Wenyan Bai Ruizhe Ji Peng Yu Wenchao Xue |
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| Affiliation: | 1 Beijing Aerospace Automatic Control Institute, Beijing 100854, China;2 School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China3 Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing 100083, China; 4 Key Laboratory of Systems and Control, Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China |
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| Abstract: | In this paper, the problem of time-varying aerodynamic parameters identification under measurement noises is studied. Byanalyzing the key aerodynamic parameters that affect the aircraft control system, a system model with extended states foridentifying equivalent aerodynamic parameters is established, and error parameters are extended to the system state, avoidingthe difficulty caused by the unknown dynamic in the system. Furthermore, an identification algorithm based on extended stateKalman filter is designed, and it is proved that the algorithm has quasi-consistency, thus, the estimation error can be evaluatedin real time. Finally, the simulation results under typical flight scenarios show that the designed algorithm can accuratelyidentify aerodynamic parameters, and has desired convergence speed and convergence precision. |
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| Keywords: | Aerodynamic parameters · Parameter identification · Extended state Kalman filter |
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