# Nonlinear System Identification: A User-Oriented Roadmap

**Authors:** Johan Schoukens, Lennart Ljung

arXiv: 1902.00683 · 2019-02-05

## TL;DR

This paper provides an accessible overview of nonlinear system identification, guiding practitioners and researchers through fundamental concepts, differences from linear methods, and practical choices with examples and intuitive explanations.

## Contribution

It offers a user-oriented roadmap that bridges linear and nonlinear system identification, emphasizing practical understanding and decision-making for diverse applications.

## Key findings

- Guides practitioners in nonlinear system identification
- Highlights differences between linear and nonlinear methods
- Provides practical examples and intuitive explanations

## Abstract

The goal of this article is twofold. Firstly, nonlinear system identification is introduced to a wide audience, guiding practicing engineers and newcomers in the field to a sound solution of their data driven modeling problems for nonlinear dynamic systems. In addition, the article also provides a broad perspective on the topic to researchers that are already familiar with the linear system identification theory, showing the similarities and differences between the linear and nonlinear problem. The reader will be referred to the existing literature for detailed mathematical explanations and formal proofs. Here the focus is on the basic philosophy, giving an intuitive understanding of the problems and the solutions, by making a guided tour along the wide range of user choices in nonlinear system identification. Guidelines will be given in addition to many examples, to reach that goal.

## Full text

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## Figures

67 figures with captions in the complete paper: https://tomesphere.com/paper/1902.00683/full.md

## References

174 references — full list in the complete paper: https://tomesphere.com/paper/1902.00683/full.md

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Source: https://tomesphere.com/paper/1902.00683