@inproceedings{068b42ec0f2949dab524b6ca5e6cdb4e,
title = "An online optimization algorithm for tracking a linearly varying optimal point with zero steady-state error",
abstract = "In this paper, we develop an online optimization algorithm for solving a class of nonconvex optimization problems with a linearly varying optimal point. The global convergence of the algorithm is guaranteed using the circle criterion for the class of functions whose gradient is bounded within a sector. Also, we show that the corresponding Lur{\'e}-type nonlinear system involves a double integrator, which demonstrates its ability to track a linearly varying optimal point with zero steady-state error. The algorithm is applied to solving a time-of-arrival based localization problem with constant velocity and the results show that the algorithm is able to estimate the source location with zero steady-state error.",
author = "Alex Wu and Petersen, \{Ian R.\} and Valery Ugrinovskii and Iman Shames",
note = "Publisher Copyright: {\textcopyright} 2025 AACC.; 2025 American Control Conference, ACC 2025 ; Conference date: 08-07-2025 Through 10-07-2025",
year = "2025",
doi = "10.23919/ACC63710.2025.11108020",
language = "English",
isbn = "979-8-3503-6761-4",
series = "Proceedings of the American Control Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "930--934",
booktitle = "2025 American Control Conference, ACC 2025",
address = "United States",
}