This paper deals with the problem of designing a distributed fault detection and isolation algorithm for nonlinear large-scale systems that are subjected to multiple fault modes. To solve this problem, a network of detection nodes is deployed to monitor the monolithic system. Each node consists of an estimator with partial observation of the system’s state. The local estimator executes a distributed variation of the particle filtering algorithm; that process the local sensor measurements and the fault progression model of the system. In addition, each node communicates with its neighbors by sharing pre-processed information. The communication topology is defined using graph theoretic tools. The information fusion between the neighboring nodes is performed by a distributed average consensus algorithm to ensure the agreement on the value of the local estimates. The simulation results demonstrate the efficiency of the proposed approach.
- Dynamic Systems and Control Division
Full-Order Distributed Fault Diagnosis for Large-Scale Nonlinear Stochastic Systems
- Views Icon Views
- Share Icon Share
- Search Site
Noursadeghi, E, & Raptis, I. "Full-Order Distributed Fault Diagnosis for Large-Scale Nonlinear Stochastic Systems." Proceedings of the ASME 2015 Dynamic Systems and Control Conference. Volume 2: Diagnostics and Detection; Drilling; Dynamics and Control of Wind Energy Systems; Energy Harvesting; Estimation and Identification; Flexible and Smart Structure Control; Fuels Cells/Energy Storage; Human Robot Interaction; HVAC Building Energy Management; Industrial Applications; Intelligent Transportation Systems; Manufacturing; Mechatronics; Modelling and Validation; Motion and Vibration Control Applications. Columbus, Ohio, USA. October 28–30, 2015. V002T19A004. ASME. https://doi.org/10.1115/DSCC2015-9927
Download citation file: