Particle Filter for Fault Diagnosis and Robust Navigation of Underwater Robot

被引：79

作者：

Zhao, Bo ^{[1
]}

Skjetne, Roger ^{[1
]}

Blanke, Mogens ^{[2
,3
]}

Dukan, Fredrik ^{[1
]}

机构：

[1] Norwegian Univ Sci & Technol, Dept Marine Technol, Ctr Ships & Ocean Struct, N-7491 Trondheim, Norway

[2] Tech Univ Denmark, Dept Elect Engn, DK-2800 Lyngby, Denmark

[3] Norwegian Univ Sci & Technol, Dept Engn Cybernet, AMOS CoE, N-7491 Trondheim, Norway

来源：

IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY | 2014年 / 22卷 / 06期

关键词：

Fault diagnosis (FD); fault tolerance; particle filter (PF); remotely operated underwater vehicle (ROV); switch-mode hidden Markov model (HMM); underwater navigation; MODELS;

D O I：

10.1109/TCST.2014.2300815

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A particle filter (PF)-based robust navigation with fault diagnosis (FD) is designed for an underwater robot, where 10 failure modes of sensors and thrusters are considered. The nominal underwater robot and its anomaly are described by a switching-mode hidden Markov model. By extensively running a PF on the model, the FD and robust navigation are achieved. Closed-loop full-scale experimental results show that the proposed method is robust, can diagnose faults effectively, and can provide good state estimation even in cases where multiple faults occur. Comparing with other methods, the proposed method can diagnose all faults within a single structure, it can diagnose simultaneous faults, and it is easily implemented.

引用

页码：2399 / 2407

页数：9

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