Data-Driven Stabilization of Nonlinear Systems via Taylor’s Expansion

Meichen Guo*, Claudio De Persis, Pietro Tesi

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeChapterScientificpeer-review


Lyapunov’s indirect methodLyapunovindirect method is one of the oldest and most popular approaches to model-based controller design for nonlinear systemsNonlinearsystem. When the explicit model of the nonlinear systemNonlinearsystem is unavailable for designing such a linear controller, finite-length off-line data is used to obtain a data-based representation of the closed-loop system, and a data-driven linear control law is designed to render the considered equilibrium locally asymptotically stable. This work presents a systematic approach for data-driven linear stabilizer design for continuous-time and discrete-time general nonlinear systemsNonlinearsystem. Moreover, under mild conditions on the nonlinear dynamics, we show that the region of attractionRegion of attraction of the resulting locally asymptotically stable closed-loop system can be estimated using data.

Original languageEnglish
Title of host publicationHybrid and Networked Dynamical Systems
Subtitle of host publicationModeling, Analysis and Control
EditorsRomain Postoyan, Paolo Frasca, Elena Panteley, Luca Zaccarian
Number of pages27
ISBN (Electronic)978-3-031-49555-7
ISBN (Print)978-3-031-49554-0, 978-3-031-49557-1
Publication statusPublished - 2024

Publication series

NameLecture Notes in Control and Information Sciences
ISSN (Print)0170-8643
ISSN (Electronic)1610-7411


  • Data-driven control
  • Lyapunov stability
  • Robust control design
  • Semidefinite programming
  • Stability of nonlinear systems
  • Sum-of-square optimization


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