# Data-Driven Output Matching of Output-Generalized Bilinear and Linear   Parameter-Varying systems

**Authors:** Leander Hemelhof, Ivan Markovsky, Panagiotis Patrinos

arXiv: 2302.12800 · 2023-02-27

## TL;DR

This paper introduces a data-driven approach for output matching in output-generalized bilinear and linear parameter-varying systems, broadening control methods for nonlinear systems with practical simulation results.

## Contribution

It proposes a novel method for output matching in a broad class of nonlinear systems, including linear parameter-varying and affine systems, with a minimal parameterization of solutions.

## Key findings

- The method effectively solves output matching for the proposed system class.
- Simulations demonstrate applicability to real-life systems.
- The approach generalizes existing control techniques for nonlinear systems.

## Abstract

There is a growing interest in data-driven control of nonlinear systems over the last years. In contrast to related works, this paper takes a step back and aims to solve the output matching problem, a problem closely related to the reference tracking control problem, for a broader class of nonlinear systems called output-generalized bilinear, thereby offering a new direction to explore for data-driven control of nonlinear systems. It is shown that discrete time linear parameter-varying systems are included in this model class, with affine systems easily shown to also be included. This paper proposes a method to solve the output matching problem and offers a way to parameterize the solution set with a minimal number of parameters. The proposed model class and method are illustrated using simulations of two real-life systems.

## Full text

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## Figures

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## References

15 references — full list in the complete paper: https://tomesphere.com/paper/2302.12800/full.md

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Source: https://tomesphere.com/paper/2302.12800