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Main Authors: Zhang, Huanshui, Wang, Hongxia
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2312.01334
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author Zhang, Huanshui
Wang, Hongxia
author_facet Zhang, Huanshui
Wang, Hongxia
contents In the paper, we propose solving optimization problems (OPs) and understanding the Newton method from the optimal control view. We propose a new optimization algorithm based on the optimal control problem (OCP). The algorithm features converging more rapidly than gradient descent, meanwhile, it is superior to Newton's method because it is not divergent in general and can be applied in the case of a singular Hessian matrix. These merits are supported by the convergence analysis for the algorithm in the paper. We also point out that the convergence rate of the proposed algorithm is inversely proportional to the magnitude of the control weight matrix and proportional to the control terminal time inherited from OCP.
format Preprint
id arxiv_https___arxiv_org_abs_2312_01334
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Optimization Methods Rooting in Optimal Control
Zhang, Huanshui
Wang, Hongxia
Optimization and Control
In the paper, we propose solving optimization problems (OPs) and understanding the Newton method from the optimal control view. We propose a new optimization algorithm based on the optimal control problem (OCP). The algorithm features converging more rapidly than gradient descent, meanwhile, it is superior to Newton's method because it is not divergent in general and can be applied in the case of a singular Hessian matrix. These merits are supported by the convergence analysis for the algorithm in the paper. We also point out that the convergence rate of the proposed algorithm is inversely proportional to the magnitude of the control weight matrix and proportional to the control terminal time inherited from OCP.
title Optimization Methods Rooting in Optimal Control
topic Optimization and Control
url https://arxiv.org/abs/2312.01334