A Koopman Operator Approach for Computing and Balancing Gramians for Discrete Time Nonlinear Systems
For control theorists and engineers, this provides a novel framework to extend linear model reduction techniques to nonlinear systems via the Koopman operator.
This paper introduces a Koopman operator-based method to compute controllability and observability gramians for nonlinear discrete-time systems, enabling balanced truncation for model reduction. The approach is demonstrated on an example nonlinear system.
In this paper, we consider the problem of quantifying controllability and observability of a nonlinear discrete time dynamical system. We introduce the Koopman operator as a canonical representation of the system and apply a lifting technique to compute gramians in the space of full-state observables. We illustrate the properties of these gramians and identify several relationships with canonical results on local controllability and observability. Once defined, we show that these gramians can be balanced through a change of coordinates on the observables space, which in turn allows for direct application of balanced truncation. Throughout the paper, we highlight the aspects of our approach with an example nonlinear system.