Nonlinear Observability via Koopman Analysis: Characterizing the Role of Symmetry
For control theorists and practitioners, this work offers a principled method to diagnose and overcome observability loss due to symmetry in nonlinear systems.
This paper develops a Koopman operator framework to analyze observability in nonlinear systems, showing that symmetry causes repeated Koopman eigenvalues leading to unobservability. The framework provides conditions for the minimum number of measurements needed to achieve observability, demonstrated on a network of nano-electromechanical oscillators.
This paper considers the observability of nonlinear systems from a Koopman operator theoretic perspective--and in particular--the effect of symmetry on observability. We first examine an infinite-dimensional linear system (constructed using independent Koopman eigenfunctions) such that its observability is equivalent to the observability of the original nonlinear system. Next, we derive an analytic relation between symmetry and nonlinear observability; it is shown that symmetry in the nonlinear dynamics is reflected in the symmetry of the corresponding Koopman eigenfunctions, as well as presence of repeated Koopman eigenvalues. We then proceed to show that the loss of observability in symmetric nonlinear systems can be traced back to the presence of these repeated eigenvalues. In the case where we have a sufficient number of measurements, the nonlinear system remains unobservable when these functions have symmetries that mirror those of the dynamics. The proposed observability framework provides insights into the minimum number of the measurements needed to make an unobservable nonlinear system, observable. The proposed results are then applied to a network of nano-electromechanical oscillators coupled via a symmetric interaction topology.