An online optimization algorithm for tracking a linearly varying optimal point with zero steady-state error

Autor:	Alex, Wu, Petersen, Ian R., Ugrinovskii, Valery, Shames, Iman
Rok vydání:	2024
Předmět:	Mathematics - Optimization and Control Electrical Engineering and Systems Science - Systems and Control 93D09
Druh dokumentu:	Working Paper
Popis:	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. Comment: 8 pages, 7 figures, submitted to 2025 American Control Conference
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2411.01826 Zobrazit plný text záznamu View this record from Arxiv