Bayesian Inference for Nonlinear Dynamical Systems : Applications and Software Implementation
Författare
Summary, in English
The common theme for all the work presented is the pyParticleEst software framework, which has been developed by the author. It is a generic software framework to assist in the application of particle methods to new problems, and to make it easy to implement and test new methods on existing problems. The theoretical contributions are extensions to existing methods, specifically the Auxiliary Particle Filter and the Metropolis Hastings Improved Particle Smoother, to handle mixed linear/nonlinear models using Rao Blackwellized methods. This work was motivated by the desire to have a coherent set of methods and model-classes in the software framework so that all algorithms can be applied to all applicable types of models.
There are three applications of these methods discussed in the thesis. The first is the modeling of periodic autonomous signals by describing them as the output of a second order system. The second is nonlinear grey-box system identification of a quadruple-tank laboratory process. The third is simultaneous localization and mapping for indoor navigation using ultrasonic range-finders.
Avdelning/ar
Publiceringsår
2015
Språk
Engelska
Publikation/Tidskrift/Serie
PhD Thesis TFRT-1107
Fulltext
- Available as PDF - 5 MB
- Available as PDF - 144 kB
- Download statistics
Dokumenttyp
Doktorsavhandling
Förlag
Department of Automatic Control, Lund Institute of Technology, Lund University
Ämne
- Control Engineering
Nyckelord
- Indoor Navigation
- pyParticleEst
- Software Implementation
- Simultaneous Localization and Mapping
- Parameter Estimation
- System Identification
- Sequential Importance Sampling
- Particle Filter
- Bayesian Inference
- Markov Chain Monte Carlo
- Particle Smoother
Status
Published
Handledare
ISBN/ISSN/Övrigt
- ISSN: 0280-5316
- ISSN: 0280-5316
- ISBN: 978-91-7623-324-5
- ISBN: 978-91-7623-323-8
Försvarsdatum
15 juni 2015
Försvarstid
10:15
Försvarsplats
Lecture hall M:B, Ole Römers väg 1, Faculty of Engineering LTH, Lund
Opponent
- Lennart Svensson (Docent)