Extending the Best Linear Approximation Framework to the Process Noise Case

TL;DR

This paper extends the Best Linear Approximation framework to include process noise, enhancing its applicability to real-world systems while maintaining core properties and analyzing effects on estimation methods.

Contribution

It generalizes the BLA framework to account for process noise in both open-loop and closed-loop systems, preserving key properties and analyzing estimation impacts.

Findings

BLA framework is extended to include process noise.

Core properties of BLA remain valid with process noise.

Impact on robust BLA estimation is analyzed.

Abstract

The Best Linear Approximation (BLA) framework has already proven to be a valuable tool to analyze nonlinear systems and to start the nonlinear modeling process. The existing BLA framework is limited to systems with additive (colored) noise at the output. Such a noise framework is a simplified representation of reality. Process noise can play an important role in many real-life applications. This paper generalizes the Best Linear Approximation framework to account also for the process noise, both for the open-loop and the closed-loop setting, and shows that the most important properties of the existing BLA framework remain valid. The impact of the process noise contributions on the robust BLA estimation method is also analyzed.