通过电动鱼食优化器为非线性管蒸汽冷凝器系统提供一种新的压力控制方法
Serdar Ekinci1, Cebrail Turkeri1, Davut Izci2,3
1Department of Computer Engineering, Batman University, Batman, 72100, Turkey.
Scientific reports
|March 4, 2025
概括
通过电捕食优化器 (EEFO) 优化的新级联PI-PDN控制策略显著改善了发电厂的蒸汽冷凝器压力控制,提高了稳定性和性能.
科学领域:
- 控制系统工程 控制系统工程
- 在工程领域的人工智能.
- 热电厂运营 热电厂运营
背景情况:
- 在管蒸汽冷凝器中,精确的压力控制对于热电厂的效率至关重要.
- 传统的控制器 (PI,PD,PID) 和调方法 (Ziegler-Nichols,Cohen-Coon) 具有非线性和干扰的局限性,导致性能差.
- 现有的元启发算法和先进控制器 (FOPID) 显示在冷凝器压力调节方面有改进的空间.
研究的目的:
- 提出一种新的级联PI-PDN控制策略,用于增强蒸汽冷凝器压力控制.
- 为了优化控制器参数,使用电捕食优化器 (EEFO),一个生物启发的算法.
- 为了验证EEFO优化的控制器对最近的元启发算法和文档研究的有效性.
主要方法:
- 实施一个级联的PI-PDN控制结构.
- 使用电动鱼食优化器 (EEFO) 优化控制器参数.
- 对最先进的元启发算法 (SMA,GEO,KMA,QIO) 和记录的控制策略 (FOPID,PI) 的比较性能分析.
主要成果:
- 基于EEFO的控制器在调节冷凝器压力方面表现出优异的性能,与其他元启发算法相比.
- 模拟结果显示,结算时间减少了22.7%,超额交易减少了78.7%,ITAE减少了81.2%.
- 拟议的控制器实现了稳定状态误差的三级降低,表明了高精度.
结论:
- 优化了EEFO的级联PI-PDN控制器提供了更快的融合,提高了对干扰的稳定性和精确的跟踪能力.
- 这种方法为现实世界热电站应用提供了高度有效的解决方案.
- 该研究为基于优化的控制策略做出了贡献,并强调了生物灵感算法的潜力在工业控制系统中.
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