Abstract
This paper studies the fault detection for linear multi-agent systems, in which the uncertainties, including random noises and bounded disturbances, are taken into account. To design the fault detection filters, a singular system is constructed by augmenting the disturbances with the system states. For each agent, a distributed filter is designed by using the states of neighbors with the aim of generating the needed fault detection residual. Moreover, the minimum upper bound of the residual under the health case is derived and used as the fault detection threshold. Due to the data transmission between agents, any agent can detect the fault either in itself or its neighbor agents. Simulation results for the theoretical work are given to demonstrate the fault detection performance.
This work is supported by National Nature Science Foundation of China under Grant 61922042 and 61773201, the 111 project (B20007), Qing Lan Project, and in part by the Fundamental Research Funds for the Central Universities under Grant NC2020002 and NP2020103.
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Ju, K., Jiang, B., Xue, Y., Mao, Z. (2022). Fault Detection for Uncertain Linear Multi-agent Systems via Distributed Filtering Algorithm. In: Yan, L., Duan, H., Yu, X. (eds) Advances in Guidance, Navigation and Control . Lecture Notes in Electrical Engineering, vol 644. Springer, Singapore. https://doi.org/10.1007/978-981-15-8155-7_168
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