ANFIS-based Measurement Information Anomaly Detection Method for Multi-AUV Cooperative Localization System

被引：0
|
作者：
Xu B. [1 ]
Li S.-X. [1 ]
Wang L.-Z. [1 ]
Wang Q.-D. [1 ]
机构：
[1] College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin
来源：
Zidonghua Xuebao/Acta Automatica Sinica | 2023年 / 49卷 / 09期
基金：
中国国家自然科学基金;
关键词：
acoustic ranging; adaptive neuro-fuzzy inference system (ANFIS); Autonomous underwater vehicle (AUV); cooperative localization; measurement anomaly;
D O I：
10.16383/j.aas.c200921
中图分类号：
学科分类号：
摘要：
In this paper, a measurement anomaly detection method based on adaptive neuro-fuzzy inference system (ANFIS) is proposed to address the problem that abnormal underwater acoustic ranging information has adverse effects on the multi autonomous underwater vehicles (AUV) cooperative localization system and the traditional fault detection methods have low detection efficiency when the multi acoustic ranging information is alternately confused. Firstly, the ANFIS model corresponding to each underwater acoustic ranging system is established. Secondly, the characteristic information reflecting the measurement anomaly, which is based on adaptive cubature Kalman filter (ACKF) and Mahalanobis distance, is used as the input of ANFIS. Then we established an initial hybrid database of pre-defined abnormal measurement information to train ANFIS model to realize online real-time detection and isolation of measurement anomalies. Finally, the lake test data are used to verify the AUV cooperative localization simulation. The experimental results show that this method can accurately identify the abnormal situation of measurement information, as the false positive rate (FPR) and the false negative rate (FNR) are reduced by more than 70% compared with the traditional fault detection method. © 2023 Science Press. All rights reserved.
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页码：1951 / 1966
页数：15
相关论文
共 30 条
  • [1] Xu Bo, Bai Jin-Lei, Hao Yan-Ling, Gao Wei, Liu Ya-Long, The research status and progress of cooperative navigation for multiple AUVs, Acta Automatica Sinica, 41, 3, pp. 445-461, (2015)
  • [2] Huang Y L, Zhang Y G, Wu Z M, Li N, Chambers J., A novel adaptive Kalman filter with inaccurate process and measurement noise covariance matrices, IEEE Transactions on Automatic Control, 63, 2, (2018)
  • [3] Kim J., Cooperative localization and unknown currents estimation using multiple autonomous underwater vehicles, IEEE Robotics and Automation Letters, 5, 2, pp. 2365-2371, (2020)
  • [4] Huang Y L, Zhang Y G, Xu B, Wu Z M, Chsmbers J A., A new adaptive extended Kalman filter for cooperative localization, IEEE Transactions on Aerospace and Electronic Systems, 54, 1, (2018)
  • [5] Li Y C, Wang Y Y, Yu W B., Multiple autonomous underwater vehicle cooperative localization in anchor-free environments, IEEE Journal of Oceanic Engineering, 44, 4, (2019)
  • [6] Liu W X, Wang Y J, Yin B J., Thruster tault identification based on fractal feature and multiresolution wavelet decomposition for autonomous underwater vehicle, Proceedings of the Institution of Mechanical Engineers Part E —— Journal of Process Mechanical Engineering, 231, 13, pp. 2528-2539, (2017)
  • [7] Zhang Hua-Qiang, Li Dong-Xing, Zhang Guo-Qiang, Application of hybrid chi-square test method in fault detection of integrated navigation system, Journal of Chinese Inertial Technology, 24, 5, pp. 696-700, (2016)
  • [8] Xu B, Razzaqi A A, Liu Y L., Cooperative localisation of AUVs based on huber-based robust algorithm and adaptive noise estimation, The Journal of Navigation, 72, 4, pp. 875-893, (2019)
  • [9] Guo R X, Gan Q, Zhang J W, Guo K, Dong J K., Huber cubature particle filter and online state estimation, Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 231, 3, pp. 158-167, (2017)
  • [10] Yu C Y, Xiang X B, Wilson P A, Zhang Q., Guidance-error-based robust fuzzy adaptive control for bottom following of a flight-style AUV with saturated actuator dynamics, IEEE Transactions on Cybernetics, 50, 5, pp. 1887-1899, (2020)
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