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Event-Triggered Interval Observer Fault Detection and Isolation for Multiagent Systems

Hailang Jin, Zhiqiang Zuo, Yijing Wang, Lei Cui, Zhiwei Gao

2024IEEE Transactions on Cybernetics40 citationsDOI

Abstract

This article investigates an event-triggered interval observer (ETIO) fault detection and isolation method for multiagent systems. First, an event-triggered mechanism is developed to reduce unnecessary communication transmission. Then, a distributed ETIO is designed by combining an interval observer and the proposed event-triggered mechanism. Furthermore, for achieving the desired tradeoff between the robustness to disturbances and the sensitivity to faults, the ETIO is formulated as a multiobjective optimization with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$ l_{1}$</tex-math> </inline-formula> <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$/$</tex-math> </inline-formula> <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$ H_{\infty}$</tex-math> </inline-formula> performance. Second, a bank of ETIOs are interpreted to isolate the faulty agent on a local agent using only the output information from itself and its neighbors. Comparison result with the existing method is given to highlight the superiority of our methodology. Finally, the multiunmanned aerial vehicles system is utilized as the case research, and specific simulation results are presented.

Topics & Concepts

NotationRobustness (evolution)Event (particle physics)Observer (physics)Interval (graph theory)Computer scienceAlgorithmMathematicsTheoretical computer scienceCombinatoricsArithmeticPhysicsBiochemistryChemistryGeneQuantum mechanicsDistributed Control Multi-Agent SystemsSmart Grid Security and ResilienceReinforcement Learning in Robotics
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