Decentralized fault diagnosis for heterogeneous multi-agent systems
Francesca Boem, Lorenzo Sabattini, Cristian Secchi · 2016
The paper proposes a decentralized method for fault detection and isolation in heterogeneous multi-agents systems. The agents are partitioned into independent nodes, providing the control inputs and monitoring the system, and dependent nodes, controlled by local interaction laws and subject to faults. The approach uses a decentralized state estimation algorithm allowing the independent nodes to estimate both the state of the dependent nodes and the control input components computed by the other independent nodes, in a completely decentralized way, without requiring communication among the independent nodes. Suitable detection and isolation residuals and thresholds are derived. Detectability and isolability sufficient conditions are provided. Simulation results show the effectiveness of the proposed approach.