A New Local-Model-Based Distributed Fault Diagnosis Scheme for Multi-Agent Systems with Actuator Faults

被引:13
作者
Qin, Liguo [1 ]
He, Xiao [2 ]
Zhou, Donghua [3 ]
Cui, Jian [4 ]
Li, Fei [5 ]
Wang, Guo [6 ]
机构
[1] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Beijing Natl Res Ctr Informat Sci & Technol BNRis, Dept Automat, Beijing 100084, Peoples R China
[3] Shandong Univ Sci & Technol, Coll Elect Engn & Automat, Qingdao 266590, Peoples R China
[4] Hebei Univ, Sch Cyber Secur & Comp, Baoding 071002, Peoples R China
[5] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
[6] Peking Univ, Sch Elect Engn & Comp Sci, Beijing 100871, Peoples R China
来源
IFAC PAPERSONLINE | 2018年 / 51卷 / 24期
基金
中国国家自然科学基金;
关键词
Local-model-based distributed fault diagnosis; multi-agent system; actuator faults; adaptive thresholds; NETWORK; DESIGN; ROBOTS;
D O I
10.1016/j.ifacol.2018.09.591
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the paper, a new local-model-based distributed fault diagnosis (LMDFD) scheme is proposed for multi-agent systems subject to actuator faults. The proposed LMDFD scheme consists of a distributed fault detection (DFD) unit and a distributed fault isolation (DFI) unit. A distributed fault detection residual generator (DFDRG) and a bank of distributed fault isolation residual generators (DFIRGs) are developed in each agent based on the closed-loop model of both the agent and neighbors of the agent. Each agent updates states of its DFDRG and DFIRGs by using information of itself, its neighbors, and the delayed information of its neighbors' neighbors. Moreover, adaptive fault detection and isolation thresholds are designed to deal with bounded disturbances induced by the delayed information. Based on the adaptive thresholds and the residuals of DFDRG and DFIRGs, the DFD and DFI logic are designed for each agent, respectively. Simulation results demonstrate the effectiveness of the proposed LMDFD scheme. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码:292 / 299
页数:8
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