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
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