Title :
Change detection for nonlinear systems; a particle filtering approach
Author :
Azimi-Sadjadi, Babak ; Krishnaprasad, P.S.
Author_Institution :
Rensselaer Polytech. Inst., Troy, NY, USA
Abstract :
We present a change detection method for nonlinear stochastic systems based on projection particle filtering. The statistic for this method is chosen in such a way that it can be calculated recursively while the computational complexity of the method remains constant with respect to time. We present some simulation results that show the advantages of this method compared to linearization techniques.
Keywords :
Global Positioning System; Kalman filters; computational complexity; filtering theory; inertial navigation; nonlinear systems; statistics; stochastic systems; change detection; computational complexity; integrated INS/GPS; nonlinear stochastic systems; particle filtering approach; projection particle filtering; Educational institutions; Fault detection; Filtering; Filters; Intelligent structures; Nonlinear systems; Quality control; State estimation; Statistics; Stochastic systems;
Conference_Titel :
American Control Conference, 2002. Proceedings of the 2002
Print_ISBN :
0-7803-7298-0
DOI :
10.1109/ACC.2002.1024567
