事件触发控制用于分布式变时优化
Haojin Li1, Xiaodong Cheng2, Peter van Heijster2
1Department of Mathematics, Harbin Institute of Technology, Weihai, 264209, China.
ISA transactions
|October 4, 2025
概括
本研究为实时优化问题引入了事件触发的分布式神经动力学方法. 它通过优化通信和消除黑塞矩阵反转来节省能源并减少计算.
科学领域:
- 控制系统 控制系统
- 优化理论 优化理论
- 分布式计算 (Distributed Computing) 是一种分布式计算.
背景情况:
- 分布时变优化问题 (DTOP) 需要各个代理商之间的高效协调.
- 现有的方法往往会带来高的通信和计算成本.
- 实时优化和共识对于许多应用程序至关重要.
研究的目的:
- 为DTOP提出一种新的事件触发 (ET) 分布神经动力学 (DND) 方法.
- 为了实现实时的全球成本函数优化和代理状态共识.
- 为了减少通信能量和计算复杂性.
主要方法:
- 将分布式控制器与代理通信的ET系统集成.
- 开发一种DND方法,避免了黑塞矩阵反向计算.
- 应用到一个电池充电问题案例研究.
主要成果:
- 拟议的ET-DND方法有效地实时优化了全球成本函数.
- 代理状态被成功地引导到达共识.
- 证明了显著的节能和计算成本降低.
结论:
- ET-DND方法为DTOP提供了一个有效的解决方案.
- 它提供了一种实用的实时优化方法,可减少资源使用.
- 该方法通过其成功应用到电池充电优化的方法得到了验证.
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