Theses and Dissertations
Issuing Body
Mississippi State University
Advisor
Cheng, Yang
Committee Member
Xin, Ming
Committee Member
Li, Pan
Date of Degree
8-15-2014
Original embargo terms
MSU Only Indefinitely
Document Type
Graduate Thesis - Campus Access Only
Major
Aerospace Engineering
Degree Name
Doctor of Philosophy
College
James Worth Bagley College of Engineering
Department
Department of Aerospace Engineering
Abstract
In science and engineering research, filtering or estimation of system’s states is widely used and developed, so the structure of a new nonlinear filter is proposed. This thesis focuses on the procedures of propagation and update step of the new filter. The algorithms used in the filter, including generalized Polynomial Chaos Algorithms, Markov Chain Monte Carlo algorithms, and Gaussian Mixture Model algorithms, are introduced. Then, the propagation and update step of the proposed filter are applied in solving two nonlinear problems: Van der Pol Oscillator and Two Body System. The simulation shows that the results of the propagation and update step are reasonable and their designs are valuable for further tests. The propagation step has the same accuracy level compared with a Quasi Monte Carlo simulation while using a much smaller number of points. The update step can build a useful Gaussian Mixture Model as the posterior distribution.
URI
https://hdl.handle.net/11668/19876
Recommended Citation
Cai, Sheng, "Generalized Polynomial Chaos and Markov Chain Monte Carlo Methods for Nonlinear Filtering" (2014). Theses and Dissertations. 2384.
https://scholarsjunction.msstate.edu/td/2384