@inproceedings{dac07d099b3740ab96397541ed4f01ae,
title = "Model reduction of nonlinear systems subject to input disturbances",
abstract = "The method of convex optimization is used as a tool for model reduction of a class of nonlinear systems in the presence of disturbances. It is shown that under some conditions the nonlinear disturbed system can be approximated by a reduced order nonlinear system with similar disturbance-output properties to the original plant. The proposed model reduction strategy preserves the nonlinearity and the input disturbance nature of the model. It guarantees a sufficiently small error between the outputs of the original and the reduced-order systems, and also maintains the properties of input-to-state stability. The matrices of the reduced order system are given in terms of a set of linear matrix inequalities (LMIs). The paper concludes with a demonstration of the proposed approach on model reduction of a nonlinear electronic circuit with additive disturbances.",
keywords = "Linear Matrix Inequalities (LMIs), Model reduction, convex optimization technique, disturbances, input-to-state stability, nonlinear systems",
author = "Ibrahima N'Doye and Laleg-Kirati, {Taous Meriem}",
note = "Publisher Copyright: {\textcopyright} 2017 American Automatic Control Council (AACC).; 2017 American Control Conference, ACC 2017 ; Conference date: 24-05-2017 Through 26-05-2017",
year = "2017",
month = jun,
day = "29",
doi = "10.23919/ACC.2017.7963486",
language = "English (US)",
series = "Proceedings of the American Control Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3488--3493",
booktitle = "2017 American Control Conference, ACC 2017",
address = "United States",
}