Title :
Estimation of States of Nonlinear Systems using a Particle Filter
Author :
Imtiaz, Syed A. ; Roy, Kallol ; Huang, Biao ; Shah, Sirish L. ; Jampana, Phanindra
Author_Institution :
Alberta Univ., Edmonton
Abstract :
Particle filters can estimate the states of nonlinear and non-Gaussian systems without any approximation when the number of particles tends to infinity. However, the method is not popular in industry because the implementation details are missing in the literature. In this paper we discuss several implementation issues and propose novel techniques for tuning the particle filter and dealing with multi-rate data. The performance of the proposed methodologies are demonstrated using a simulated non-linear CSTR and an experimental four tank system.
Keywords :
nonlinear control systems; particle filtering (numerical methods); process control; state estimation; CSTR; four tank system; multirate data; nonGaussian system; nonlinear system; particle filter tuning; process control; state estimation; Chemical engineering; Chemical processes; Density functional theory; Filtering; Gaussian noise; Noise measurement; Nonlinear equations; Nonlinear systems; Particle filters; State estimation;
Conference_Titel :
Industrial Technology, 2006. ICIT 2006. IEEE International Conference on
Conference_Location :
Mumbai
Print_ISBN :
1-4244-0726-5
Electronic_ISBN :
1-4244-0726-5
DOI :
10.1109/ICIT.2006.372687
