Skip to content

Region of Attraction Estimation of Quadratic Systems using Valley Quadratic Constraints

License

Notifications You must be signed in to change notification settings

SCLiao47/ValleyQC_ROA

Repository files navigation

Quadratic Constraints for Local Stability Analysis of Quadratic Systems

This repository contains the numerical results of paper "Quadratic Constraints for Local Stability Analysis of Quadratic Systems" by Shih-Chi Liao, Maziar S. Hemati, Peter Seiler, published at IEEE Conference on Decision and Control 2022 in Cancun, Maxico.

[Paper on IEEE] / [Paper on arXiv] / [Slides] / [Poster]

alt text

Abstract

This paper proposes new quadratic constraints (QCs) to bound a quadratic polynomial. Such QCs can be used in dissipation inequalities to analyze the stability and performance of nonlinear systems with quadratic vector fields. The proposed QCs utilize the sign-indefiniteness of certain classes of quadratic polynomials. These new QCs provide a tight bound on the quadratic terms along specific directions. This reduces the conservatism of the QC bounds as compared to the QCs in previous work. Two numerical examples of local stability analysis are provided to demonstrate the effectiveness of the proposed QCs.

BibTex

If you find this project helpful, please cite the following reference:

@inproceedings{liao2022quadratic,
  title={Quadratic constraints for local stability analysis of quadratic systems},
  author={Liao, Shih-Chi and Hemati, Maziar S and Seiler, Peter},
  booktitle={2022 IEEE 61st Conference on Decision and Control (CDC)},
  pages={7053--7058},
  year={2022},
  organization={IEEE},
  doi={10.1109/CDC51059.2022.9992343}
}

About

Region of Attraction Estimation of Quadratic Systems using Valley Quadratic Constraints

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages