Fault factor and multiple observers based AUV actuator fault isolation and identification

被引：0
|
作者：
Wu Y.-K. [1 ]
Hu D.-H. [1 ]
Fu J. [2 ]
Zhou Y. [3 ]
机构：
[1] College of Automation, Jiangsu University of Science and Technology, Zhenjiang
[2] State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang
[3] School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang
来源：
Kongzhi yu Juece/Control and Decision | 2024年 / 39卷 / 06期
关键词：
actuator; AUV; fault factor; fault isolation; multi-level fault identification; multiple observers;
D O I：
10.13195/j.kzyjc.2022.2040
中图分类号：
学科分类号：
摘要：
The actuator reliability is of great significance to the system security. Therefore, a fault isolation and identification method is proposed for autonomous underwater vehicles (AUVs) based on fault factor and multiple observers scheme. Firstly, the fault isolation and identification of AUV actuators is divided into two levels based on the concept of fault factors. Then, the fault isolations focusing on rudders, propellers and actuators based on extended state observers (ESOs) and isolation logic rules are proposed. According to the relationship between the output force and torque, further identification can be realized via internal information analysis of fault factors. The simulation results show that the proposed scheme has an outstanding accuracy for AUV actuator fault isolation and identification. © 2024 Northeast University. All rights reserved.
引用
收藏
页码：2005 / 2012
页数：7
相关论文
共 16 条
  • [1] Zhu D Q, Hu Z., Fault diagnosis and fault-tolerant control technology of underwater vehicle, pp. 1-20, (2012)
  • [2] Alexander Z, Alexey Z, Vladimir F., Fault identification in underwater vehicle thrusters via sliding mode observers, International Journal of Applied Mathematics and Computer Science, 30, 4, pp. 679-688, (2020)
  • [3] Wang X H., Active fault tolerant control for unmanned underwater vehicle with actuator fault and guaranteed transient performance, IEEE Transactions on Intelligent Vehicles, 6, 3, pp. 470-479, (2021)
  • [4] Nejati Z, Faraji A, Abedi M., Robust three stage central difference Kalman filter for helicopter unmanned aerial vehicle actuators fault estimation, International Journal of Engineering, 34, 5, pp. 1290-1296, (2021)
  • [5] Zhu D Q, Sun B., Information fusion fault diagnosis method for unmanned underwater vehicle thrusters, IET Electrical Systems in Transportation, 3, 4, pp. 102-111, (2013)
  • [6] Chen X Q, Sun R, Wang F, Et al., Two-stage unscented Kalman filter algorithm for fault estimation in spacecraft attitude control system, IET Control Theory & Applications, 12, 13, pp. 1781-1791, (2018)
  • [7] Chatterjee S, Sadhu S, Ghoshal T K., Fault detection and identification of non-linear hybrid system using self-switched sigma point filter bank, IET Control Theory & Applications, 9, 7, pp. 1093-1102, (2015)
  • [8] Liu F Q, Long Y, Luo J, Et al., Active fault localization of actuators on torpedo-shaped autonomous underwater vehicles, Sensors, 21, 2, (2021)
  • [9] Yu D C, Zhu C G, Zhang M J, Et al., Experimental study on multi-domain fault features of AUV with weak thruster fault, Machines, 10, 4, pp. 236-252, (2022)
  • [10] Liu W X, Wang Y J, Yin B J, Et al., Thruster fault identification based on fractal feature and multiresolution wavelet decomposition for autonomous underwater vehicle, Proceedings of the Institution of Mechanical Engineers — Part C: Journal of Mechanical Engineering Science, 231, 13, pp. 2528-2539, (2017)
12