4.7 Article

Distributed Fault Detection and Isolation for Multiagent Systems: An Interval Observer Approach

Journal

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
Volume 50, Issue 6, Pages 2220-2230

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMC.2018.2811390

Keywords

Observers; Fault detection; Vehicle dynamics; Multi-agent systems; Sensitivity; Fault detection (FD); fault isolation (FI); interval observer; multiagent systems (MASs)

Funding

  1. National Natural Science Foundation of China [61621004, 61420106016]
  2. Research Fund of the State Key Laboratory of Synthetical Automation for Process Industries [2013ZCX01]

Ask authors/readers for more resources

This paper presents a distributed method for detecting and isolating the faults in multiagent systems (MASs). First, for the output-feedback-based closed-loop MAS in normal case and faulty cases, a bank of fault detection and isolation (FDI) interval observers are constructed by taking into account the outputs of local and received from neighbors, the bounds of one node fault signal and the whole disturbances. Then, the observer gains can be determined by solving the disturbance attenuation, fault sensitivity, and nonnegativity conditions, simultaneously. Furthermore, an alarm signal is released when the zero value is excluded from any one of the intervals, a node fault is indicated when the zero value is included in one residual interval and excluded from the surplus intervals. Different from the classical FDI methods, the proposed interval observers are able to both generate the residual signals and imply the thresholds. Under such framework, each agent has the capacity to determine which neighbor agent is faulty. Finally, the developed techniques are demonstrated in a simulation example.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available