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在通信故障下城市排水系统控制中神经进化的稳定性:比较集中和分散的控制方案

Shengwei Pei¹, Guangtao Fu¹, Lan Hoang²

¹Centre for Water Systems, Department of Engineering, University of Exeter EX4 4QF, UK.

|May 2, 2025

概括

神经进化增强了城市排水系统的实时控制 (RTC),减少了洪水和综合下水道溢出 (CSO) 泄漏. 与基线策略相比,集中式和分散式方法都显示出对通信故障的更强的稳定性.

科学领域:

环境工程环境工程
人工智能的人工智能
控制系统控制系统

背景情况:

实时控制 (RTC) 对城市排水系统至关重要,以减轻洪水和综合下水道溢出 (CSO) 泄漏.
神经进化证明了RTC的潜力,但它对通信系统故障的弹性需要彻底调查.
了解通信中断的影响对于制定强有力的控制策略至关重要.

研究的目的:

在各种通信故障场景下,评估城市排水系统中神经进化RTC的稳定性.
为了比较集中和分散的神经进化控制方案的性能.
评估短暂和长期通信中断对系统性能的影响.

主要方法:

在Astlingen基准测试网络上进行了模拟.
神经进化算法应用于集中和分散的控制方案.
通信故障包括暂时的观察/行动中断和长时间的传感器断开连接.

主要成果:

集中式神经进化超过了分散式神经进化和平等填充度 (EFD) 基线在总CSO体积减少方面.
集中神经进化显示出对观察通信中断和传感器断开连接的更大稳定性.
分散的神经进化在处理动作通信中断和在传感器断开连接时保持局部稳定方面表现出色.
与EFD策略相比,这两种神经进化方法都表现出优越的弹性和降低的性能变化.

结论:

神经进化RTC策略在城市排水系统的管理中提供了显著的改进,即使在通信故障的情况下.
集中和分散的神经进化具有不同的稳定性优势,取决于通信中断的性质.
这些发现有助于通过先进的控制技术设计更有弹性的城市排水系统.

关键词:

集中的中央控制控制.综合下水道溢出情况通信故障通信故障分散的控制控制去中心化.神经进化是一种神经进化.实时控制实时控制

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