组合粒子群优化和强化学习用于水库水位控制
Oana Niculescu-Faida1, Catalin Popescu1
1Hydrotechnical Engineering Department, System Engineering-Automation and Applied Informatics Domain, Faculty of Hydrotechnics, Technical University of Civil Engineering Bucharest, Blvd. Lake Tei No. 122-124, Sector 2, 020396 Bucharest, Romania.
Sensors (Basel, Switzerland)
|August 28, 2025
概括
这项研究介绍了水库水位的先进自适应控制系统,它结合了强化学习和粒子群优化来防止洪水. 该系统已成功实施,在现实应用中展示了有效的洪水缓解.
科学领域:
- 工程
- 环境科学
- 控制系统
背景情况:
- 工业PID控制器提供稳定性,但由于操作变化需要经常重新调整.
- 对于周边地区的防洪, 水库水位的调节至关重要.
研究的目的:
- 开发一个最佳的自动水库水位调节系统.
- 通过自适应地调整PID控制器参数来增强洪水控制.
主要方法:
- 一种结合强化学习和粒子群优化 (PSO) 的新型优化方法.
- 开发了一个数学方程式来指导PSO,增强强化学习的适应性功能.
- 使用MATLAB和Python进行模拟.
主要成果:
- 开发的控制系统有效地结合了强化学习和PSO的优势,最大限度地减少了它们的缺点.
- 模拟结果非常好, 验证了系统的性能.
- 该系统已成功实施,并展示了实际的防洪能力.
结论:
- 适应式PID控制器参数调整系统为水库水位管理提供了强大的解决方案.
- 开发的水最佳自动化系统应在罗马尼亚实施并适应更广泛的使用.
- 这项研究有助于通过智能自动化改进洪水控制策略.
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