Informativity of Data-Knowledge Pairs for Lyapunov Equations

TL;DR

This paper characterizes the informativity of data-knowledge pairs for solving Lyapunov equations, extending existing concepts to incorporate various prior system knowledge.

Contribution

It introduces a new notion of joint informativity, derives an algebraic condition, and analyzes special cases for data-driven Lyapunov equation solutions.

Findings

Introduces joint informativity for data-knowledge pairs.

Provides an algebraic condition for joint informativity.

Analyzes special cases with prior knowledge.

Abstract

In the past few years, data informativity with prior knowledge has attracted increasing attention. This line of research aims to characterize a dataset on a dynamical system that enables system analysis or design only by the dataset and given prior knowledge on the system. In this paper, we investigate such a characterization for the data-driven problem of computing a unique solution to Lyapunov equations. First, we introduce a notion of joint informativity for data-knowledge pairs as an extension of the standard informativity concept. Second, we derive an algebraic equivalent condition for the joint informativity. Finally, we provide further insights into the joint informativity by considering a special case of prior knowledge. The characterization presented in this paper is developed for a wide class of prior knowledge, enabling the incorporation of various forms of system information.