Work

Formulas for Data-Driven Control: Stabilization, Optimality, and Robustness

Year: 2019

Type: article

Abstract: In a paper by Willems et al., it was shown that persistently exciting data can be used to represent the input-output behavior of a linear system. Based on this fundamental result, we derive a parametrization of linear feedback systems that paves the way to solve important control problems using data-dependent linear matrix inequalities only. The result is remarkable in that no explicit system's matrices identification is required. The examples of control problems we solve include the state and output feedback stabilization, and the linear quadratic regulation problem. We also discuss robustness to noise-corrupted measurements and show how the approach can be used to stabilize unstable equilibria of nonlinear systems.

Source: IEEE Transactions on Automatic Control

DOI: 10.1109/tac.2019.2959924

Authors: Claudio De Persis, Pietro Tesi

Institutions: University of Groningen, University of Florence

Language: English

Topic: Control Systems and Identification

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,045

OpenAlex ID: W2972180738

FWCI: 27.86

Cites: 47

Cited by: 1,050

Related to: 10