Data-driven harmonic output regulation of a class of nonlinear systems

TL;DR

This paper introduces a data-driven approach for designing state-feedback controllers that solve the output regulation problem for nonlinear systems, using a semidefinite program to directly compute the controller from data.

Contribution

It develops a novel data-dependent semidefinite programming method for output regulation in nonlinear systems, extending model-based techniques and improving upon existing linear system results.

Findings

Successfully designed controllers that achieve output regulation in nonlinear systems.

The method outperforms existing approaches when applied to linear systems.

Numerical simulations validate the effectiveness of the proposed data-driven control design.

Abstract

The paper deals with the data-based design of state-feedback controllers that solve the output regulation problem for a class of nonlinear systems. Inspired by recent developments in model-based output regulation design techniques and in data-driven control design for nonlinear systems, we derive a data-dependent semidefinite program that, when solved, directly returns a controller that steers the regulation error to a periodic signal whose Fourier series has identically zero coefficients up to a certain order set by the controller. When specialized to the case of linear systems, the result appears to improve upon existing work. Numerical results illustrate the findings