Sequential Bayesian Inference for Uncertain Nonlinear Dynamic Systems

A Sequential Bayesian Inference tutorial for the solution of state, state-parameter and input-state-parameter estimation problems in uncertain nonlinear dynamic systems on the basis of sparse measurements.

Algorithms

• Unscented Kalman Filter (UKF)
• Particle Filter (PF)
• Particle Filter with Mutation (MPF)
• Sigma-Point Particle Filter (SPPF)
• Gaussian-Mixture Sigma-Point Particle Filter (GMSPPF)
• Rao-Blackwelised Particle Filter (RBPF)
• Dual Kalman Filter - Unscented Kalman Filter (DKF-UKF)

Getting started

Pull down a copy by downloading or cloning the repository

git clone https://github.com/ETH-WindMil/JSD-SBI ~/JSD-SBI

Cite as

Konstantinos E. Tatsis, Vasilis K. Dertimanis & Eleni N. Chatzi, «Sequential Bayesian Inference for Uncertain Nonlinear Dynamic Systems: A Tutorial.», Journal of Structural Dynamics, Issue 1 https://popups.uliege.be/2684-6500/index.php?id=107.

Found a Bug?

If you think you've found a bug, go ahead and create a new GitHub issue. Be sure to include as much information as possible so that we can reproduce the bug.