Carleman Linearization of Nonlinear Systems and Its Finite-Section Approximations

TL;DR

This paper analyzes Carleman linearization for nonlinear systems, providing explicit error bounds for finite-section approximations and demonstrating exponential convergence, which aids in control and safety verification tasks.

Contribution

The paper establishes explicit error bounds and proves exponential convergence of finite-section Carleman linearization for nonlinear systems.

Findings

Finite-section approximations converge exponentially to the nonlinear system.

Error bounds can be used to determine truncation lengths for practical applications.

Validation through simulations confirms theoretical results.

Abstract

The Carleman linearization is one of the mainstream approaches to lift a finite-dimensional nonlinear dynamical system into an infinite-dimensional linear system with the promise of providing accurate approximations of the original nonlinear system over larger regions around the equilibrium for longer time horizons with respect to the conventional first-order linearization approach. Finite-section approximations of the lifted system has been widely used to study dynamical and control properties of the original nonlinear system. In this context, some of the outstanding problems are to determine under what conditions, as the finite-section order (i.e., truncation length) increases, the trajectory of the resulting approximate linear system from the finite-section scheme converges to that of the original nonlinear system and whether the time interval over which the convergence happens can be quantified explicitly. In this paper, we provide explicit error bounds for the finite-section approximation and prove that the convergence is indeed exponential with respect to the finite-section order. For a class of nonlinear systems, it is shown that one can achieve exponential convergence over the entire time horizon up to infinity. Our results are practically plausible as our proposed error bound estimates can be used to compute proper truncation lengths for a given application, e.g., determining proper sampling period for model predictive control and reachability analysis for safety verifications. We validate our theoretical findings through several illustrative simulations.