Fixed-Time Gradient Dynamics With Time-Varying Coefficients for Continuous-Time Optimization

被引：23

作者：

Nguyen, Lien T. T. ^{[1
]}

Yu, Xinghuo ^{[2
]}

Eberhard, Andrew ^{[1
]}

Li, Chaojie ^{[3
]}

机构：

[1] RMIT Univ, Sch Sci, Melbourne, Vic 3000, Australia

[2] RMIT Univ, Sch Engn, Melbourne, Vic 3000, Australia

[3] Univ New South Wales, Sch Elect Engn & Telecommun, Sydney, NSW 2033, Australia

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2023年 / 68卷 / 07期

基金：

澳大利亚研究理事会;

关键词：

Continuous-time optimization; fixed-time convergence; gradient-based method; Lyapunov function; Newton-like method; stability; time-varying systems; STABILITY; STABILIZATION; NETWORKS; FLOWS;

D O I：

10.1109/TAC.2022.3206251

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this article, we propose fixed-time gradient dynamics with time-varying coefficients for continuous-time optimization. We first investigate the Lyapunov stability conditions that allow us to achieve fixed-time stability of the time-varying dynamical systems. We then use them to deal with continuous-time optimization problems. We show that under the proposed fixed-time gradient dynamics and by choosing time-varying coefficients, the searching trajectories converge to their optima in fixed-time from any initial points with a very fast rate. Simulation results are given to show the effectiveness of the proposed fixed-time gradient dynamics with tunable time-varying coefficients for continuous-time optimization.

引用

页码：4383 / 4390

页数：8

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