分布式时变优化的无hessian固定/预定义时间算法

IF 8.7 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Zeng-Di Zhou;Ge Guo;Renyongkang Zhang
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引用次数: 0

摘要

本文针对时不变和时变优化(TVO)问题,提出了不受Hessian约束的分布式算法。为此,引入了以分布式平均跟踪方式估计系统梯度和的子系统,并在此基础上设计了将梯度和下降法与状态一致性方案相结合的分布式协议。此外,在我们的TVO方法中,引入了一个范数归一化的sgn函数来利用系统的不连续来补偿系统的内部漂移。这些方法是有趣的,因为它们可以在特定时间内独立于系统的初始状态实现优化目标,即满足固定/预定义时间的收敛性。此外,提出了一种完全分布的自适应增益方法,避免了获取一些全局信息。数值模拟和实例分析验证了所提算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hessian-Free Fixed-/Predefined-Time Algorithms for Distributed Time-Varying Optimization
This article proposes distributed algorithms free of Hessian for both time-invariant and time-varying optimization (TVO) problems. To this end, a subsystem is introduced to estimate the system’s gradient-sum in a distributed average tracking manner, based on which a distributed protocol is designed by coupling the gradient-sum descent method and state consensus scheme. Additionally, in our TVO method, a norm-normalized signum function is introduced to compensate for the internal drift of the system using its discontinuity. These methods are interesting as they can achieve the optimization goal within a specific time independent of system’s initial states, i.e., satisfy fixed-/predefined-time convergence. Moreover, a fully distributed adaptive gain method is proposed to avoid obtaining some global information. The numerical simulation and case study are provided to corroborate the effectiveness of proposed algorithms.
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来源期刊
IEEE Transactions on Systems Man Cybernetics-Systems
IEEE Transactions on Systems Man Cybernetics-Systems AUTOMATION & CONTROL SYSTEMS-COMPUTER SCIENCE, CYBERNETICS
CiteScore
18.50
自引率
11.50%
发文量
812
审稿时长
6 months
期刊介绍: The IEEE Transactions on Systems, Man, and Cybernetics: Systems encompasses the fields of systems engineering, covering issue formulation, analysis, and modeling throughout the systems engineering lifecycle phases. It addresses decision-making, issue interpretation, systems management, processes, and various methods such as optimization, modeling, and simulation in the development and deployment of large systems.
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