Learned Lifted Linearization Applied to Unstable Dynamic Systems Enabled by Koopman Direct Encoding. (arXiv:2210.13602v1 [cs.LG])

This paper presents a Koopman lifting linearization method that is applicable
to nonlinear dynamical systems having both stable and unstable regions. It is
known that DMD and other standard data-driven methods face a fundamental
difficulty in constructing a Koopman model when applied to unstable systems.
Here we solve the problem by incorporating knowledge about a nonlinear state
equation with a learning method for finding an effective set of observables. In
a lifted space, stable and unstable regions are separated into …

arxiv encoding linearization systems