On data-driven stabilization of systems with quadratic nonlinearities
Systems and Control
2021-03-30 v1 Systems and Control
Dynamical Systems
Abstract
In this paper, we directly design a state feedback controller that stabilizes a class of uncertain nonlinear systems solely based on input-state data collected from a finite-length experiment. Necessary and sufficient conditions are derived to guarantee that the system is absolutely stabilizable and a controller is designed. Results derived under some relaxed prior information about the system and strengthened data assumptions are also discussed. Numerical examples illustrate the method with different levels of prior information.
Cite
@article{arxiv.2103.15631,
title = {On data-driven stabilization of systems with quadratic nonlinearities},
author = {Alessandro Luppi and Claudio De Persis and Pietro Tesi},
journal= {arXiv preprint arXiv:2103.15631},
year = {2021}
}