强大的模型 免费的适应性预测控制 废水处理过程的软件包丢失
IEEE transactions on cybernetics
|June 26, 2024
概括
一个新的强大的无模型自适应预测控制 (RMFAPC) 策略有效地管理废水处理过程,尽管存在外部干扰和数据包丢失. 这种先进的控制方法确保了稳定和高效的运行,优于传统方法.
科学领域:
- 环境工程 环境工程
- 控制系统工程 控制系统工程
- 过程自动化 过程自动化
背景情况:
- 废水处理过程 (WWTP) 容易因外部干扰和数据包丢失而导致性能下降.
- 现有的控制策略往往难以在这样具有挑战性的条件下保持最佳性能.
研究的目的:
- 提出一个强大的无模型自适应预测控制 (RMFAPC) 策略,并配备一个数据包丢失补偿机制 (PDCM),以提高WWTP性能.
- 确保WWTP的强有力的控制和稳定,尽管存在外部干扰和通信不确定性.
主要方法:
- 动态线性化方法 (DLA) 使用扰乱的过程数据来近似系统动态.
- 预测控制策略与扩展状态观察员 (ESO) 结合用于干扰减弱.
- 专门设计用于处理数据丢失的数据丢失补偿机制 (PDCM).
主要成果:
- 在模拟场景中,RMFAPC显著降低了整合绝对误差 (IAE) 的0.0223和0.1976.
- 与没有标准模型的自适应预测控制 (MFAPC) 相比,证明了对干扰的优越稳定性.
- 废弃实验证实了PDCM在缓解由数据包丢失引起的问题方面的有效性.
结论:
- 拟议的RMFAPC战略提供了一个强大而有效的解决方案,用于在干扰和数据包丢失的情况下控制WWTP.
- DLA,ESO和PDCM的整合确保了可靠和稳定的过程运行.
- 模拟结果验证了RMFAPC显著的性能改进和稳定性.
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