Authors: Brian Beckman
Kalman Folding 5 presents an Extended Kalman Filter in Mathematica. Python is much more accessible to average practitioners. In this follow-up article, we write a very general, foldable EKF in Python, verify it against Mathematica using sympy, Python's package for symbolic mathematics. We apply it to a spinning dashpot and demonstrate both state estimation and system identification from observing only one angle over time. It is remarkable that a complete dynamical description of eight states and parameters can be recovered from measurements of a single, scalar value.
Comments: 31 Pages. Creative Commons 4.0 license: https://creativecommons.org/licenses/by/4.0/
[v1] 2017-12-23 16:09:27
Unique-IP document downloads: 361 times
Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.
Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.