An Adjustable Parameter-Based Robust Distributed Fault Diagnosis for One-Sided Lipschitz Formation of Clustered Multi-Agent Systems

This paper addresses the challenge of distributed fault diagnosis in the context of the one-sided Lipschitz formation of agents. Each agent integrates an observer to detect and estimate both linear and non-linear faults in its attitude control subsystem. A robust design configuration is also develop...

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Bibliographic Details
Published inElectronics (Basel) Vol. 13; no. 14; p. 2759
Main Authors Barzegar, Ailin, Rahimi, Afshin
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.07.2024
Subjects
Attitude control
Configuration management
Control algorithms
Controllers
Design
Disturbances
Error reduction
Fault detection
Fault diagnosis
Investment analysis
Kalman filters
Linear matrix inequalities
Methods
Multiagent systems
Nonlinear control
Parameter robustness
Robust control
Robust design
Root-mean-square errors
Satellite constellations
Satellite observation
Satellites
State estimation
State observers
Subsystems
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Summary:This paper addresses the challenge of distributed fault diagnosis in the context of the one-sided Lipschitz formation of agents. Each agent integrates an observer to detect and estimate both linear and non-linear faults in its attitude control subsystem. A robust design configuration is also developed to account for external perturbations. The robust observer utilized in this study is an unknown input observer (UIO), designed to mitigate the impact of disturbances on fault and state estimation errors. The observer’s parameters are determined using linear matrix inequalities (LMIs). Furthermore, a UIO incorporating an adjustable parameter (AP) is introduced to enhance fault diagnosis accuracy. Simulation results for two satellite clusters, consisting of five satellites with varying dynamics due to external disturbances, are presented to validate the approach. Instead of equipping every agent with an observer, specific agents can be equipped with observers to detect faults throughout the constellation, thereby reducing computational demands in configurations with numerous agents. Finally, a comparison is made between the proposed AP-based UIO and a standard UIO. The comparison findings reveal a noteworthy average of a substantial 56.61% reduction in root mean square error (RMSE) employing AP-based UIO compared to the utilization of standard robust UIO.
ISSN:2079-9292
2079-9292
DOI:10.3390/electronics13142759