Zhiqiang Wu (Committee Member), Kefu Xue (Committee Member), Xiaodong Zhang (Advisor)
Master of Science in Engineering (MSEgr)
Fault diagnosis problems for large-scale nonlinear systems have attracted significant attentions from researchers in recent years. Most fault detection and isolation (FDI) methods have been proposed based on a centralized architecture. However, due to the complexity of the system, most of these centralized fault detection and diagnosis schemes are not able to delivery effective fault detection and isolation performance for a large-scale nonlinear system, which contains subsystems interacting with neighboring subsystems.
In this thesis, a distributed fault detection and isolation method is developed for the automated highway systems (AHS). For each subsystem of AHS, a distributed fault detection and isolation component is designed to detect and isolate a sensor fault in the system. Each component uses the local measurements and communicated information from other neighboring fault detection and isolation components. In each local subsystem of AHS, adaptive thresholds for fault detection and isolation are derived based on the distributed fault diagnosis decision scheme. Simulation results for two case studies show the effectiveness of the distributed FDI method.
Department or Program
Department of Electrical Engineering
Year Degree Awarded
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