Title :
Particle filtering based likelihood ratio approach to fault diagnosis in nonlinear stochastic systems
Author :
Li, Ping ; Kadirkamanathan, Visakan
Author_Institution :
Dept. of Autom. Control & Syst. Eng., Univ. of Sheffield, UK
fDate :
8/1/2001 12:00:00 AM
Abstract :
This paper presents the development of a particle filtering (PF) based method for fault detection and isolation (FDI) in stochastic nonlinear dynamic systems. The FDI problem is formulated in the multiple model (MM) environment, then by combining the likelihood ratio (LR) test with the PF, a new FDI scheme is developed. The simulation results on a highly nonlinear system are provided which demonstrate the effectiveness of the proposed method
Keywords :
fault diagnosis; filtering theory; nonlinear dynamical systems; simulation; stochastic systems; fault diagnosis; fault isolation; multiple model environment; particle filtering based likelihood ratio approach; stochastic nonlinear dynamic systems; Analytical models; Fault detection; Fault diagnosis; Filtering; Gaussian noise; Mathematical model; Monitoring; Nonlinear dynamical systems; Nonlinear systems; Stochastic systems;
Journal_Title :
Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
DOI :
10.1109/5326.971661
