Sequential sum-of-squares programming for analysis of nonlinear systems
Optimization and Control
2023-10-03 v1 Systems and Control
Systems and Control
Abstract
Numerous interesting properties in nonlinear systems analysis can be written as polynomial optimization problems with nonconvex sum-of-squares problems. To solve those problems efficiently, we propose a sequential approach of local linearizations leading to tractable, convex sum-of-squares problems. Local convergence is proven under the assumption of strong regularity and the new approach is applied to estimate the region of attraction of a polynomial aircraft model.
Cite
@article{arxiv.2210.02142,
title = {Sequential sum-of-squares programming for analysis of nonlinear systems},
author = {Torbjørn Cunis and Benoît Legat},
journal= {arXiv preprint arXiv:2210.02142},
year = {2023}
}
Comments
Submitted to 2023 American Control Conference