Title :
Strong Tracking Particle Filter Based Fault Diagnosis for Nonlinear Systems
Author :
Shirong, Liu ; Wenbo, He
Author_Institution :
Hangzhou Dianzi Univ., Hangzhou
Abstract :
A strong tracking particle filter is presented that is used to make fault diagnosis for nonlinear dynamic systems. Strong tracking particle filter is consisted of strong tracking filter and particle filter. Because of the uncertainty of the fault models of nonlinear dynamic system, the errors between the values of the state estimation with particle filter and ones with strong tracking particle filter are used to judge the faults of the system. Simulations show that the proposed method is capable of the fault detection and diagnosis of the systems.
Keywords :
fault diagnosis; nonlinear systems; particle filtering (numerical methods); state estimation; fault detection; fault diagnosis; nonlinear dynamic systems; state estimation; strong tracking particle filter; Automation; Fault detection; Fault diagnosis; Helium; Nonlinear dynamical systems; Nonlinear systems; Particle filters; Particle tracking; State estimation; Uncertainty; State estimation; fault detection and diagnosis; particle filter; strong tracking filter;
Conference_Titel :
Control Conference, 2007. CCC 2007. Chinese
Conference_Location :
Hunan
Print_ISBN :
978-7-81124-055-9
Electronic_ISBN :
978-7-900719-22-5
DOI :
10.1109/CHICC.2006.4347625
