Open AccessAn Active Fault Detection for Unmanned Surface Vehicles With Minor Fault
Author(s) -
Zhi-Hao Liu,
Jian-Ning Li,
Wan-Ying Yang,
Mei-Yan Shen,
Xu-Feng Shen,
Yang Luo
Publication year - 2022
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2022.3221809
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
This article proposes an active fault detection method for Unmanned Surface Vehicles (USVs) with uncertain bounded disturbance to achieve the minor faults detection of USV. In practice, minor faults are the early cases of normal faults with the characteristic of low amplitude and difficulty to detection. At first, a set-membership estimation approach is used to describe the area topology of the nominal model of USVs and the fault models. Then, an auxiliary input signal is designed to enhance the character of minor faults, and the minor faults can be separated from the considered USVs in spite of uncertain bounded disturbances. Next, the considered problem is transformed into a nonconvex optimization problem, and the optimal auxiliary signal is obtained via solving the mixed integer quadratic programming (MIQP). Finally, a case study of the USVs is used to show the effectiveness of the proposed method.