在预设时间内通过集成滑动模式控制实现受约束的优化图表
IEEE transactions on cybernetics
|September 16, 2025
概括
本研究介绍了一种新的分布式算法,用于定向图的预设时间优化. 新方法为复杂的网络优化问题提供了更快的融合和更好的稳定性.
科学领域:
- 控制系统工程 控制系统工程
- 分布式优化 分布式优化
- 网络化系统 网络化系统
背景情况:
- 在网络系统中,平等约束的优化问题至关重要.
- 现有的分布式优化算法往往缺乏精确的融合时间保证或稳定性.
- 定向图 (数图) 对分布式信息估计和共识提出了独特的挑战.
研究的目的:
- 开发一个分布式预设时间优化算法,用于对二位图的平等约束问题.
- 增强对外部干扰和网络不确定性的强度.
- 与现有的有限和固定的时间算法相比,改进融合时间精度.
主要方法:
- 开发用于全球成本函数信息的分布式预设时间估计器.
- 整合了整体的滑动模式控制,以提高强度.
- 基于估计器的分布式强大的预设时间优化算法的设计.
主要成果:
- 拟议的算法实现了精确的预设时间收.
- 在模拟中证明了对干扰的增强强性.
- 数字模拟与有限和固定时间算法相比,显示出更高的收率.
- 该算法适用于各种网络拓,包括强度连接的网络.
结论:
- 开发的基于估计器的分布式预设时间算法有效地解决了对位图的平等受约束优化.
- 该算法在趋同时间精度和稳定性方面提供了显著的改进.
- 这项工作推进了网络系统分布式优化的最新技术.
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