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A novel model-based adaptive control strategy for step-feed SBRs dealing with influent fluctuation

机译:一种基于模型的新型自适应控制策略,用于分步进料SBR处理进水波动

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摘要

A novel model-based adaptive control strategy for step-feed sequence batch reactors (SBRs) was developed and compared with traditional fixed-parameters control strategy and statically optimal parameters control strategy under influent fluctuation period. The SBR was operated with automatic alteration of the operating parameters based on the numerical calculation results of fully coupled activated sludge model (FCASM). Since the influent fluctuated from one cycle to another, model-based adaptive control strategy was applied to optimize the operating parameters of the SBR accordingly. By using the model-based adaptive control strategy, the average removal efficiencies for total nitrogen (TN) and total phosphorus (TP) achieved in fluctuation tests were over 84% and 98%, respectively. Compared to traditional fixedparameters strategy, the TN removal efficiency was improved by 25.11%.
机译:提出了一种新颖的基于模型的分步进料间歇反应器自适应控制策略,并将其与传统的固定参数控制策略和进水波动期静态最优参数控制策略进行了比较。根据完全耦合的活性污泥模型(FCASM)的数值计算结果,通过自动更改运行参数来运行SBR。由于进水从一个周期波动到另一个周期,因此应用了基于模型的自适应控制策略来相应地优化SBR的运行参数。通过使用基于模型的自适应控制策略,波动测试中获得的总氮(TN)和总磷(TP)的平均去除率分别超过84%和98%。与传统的固定参数策略相比,TN去除效率提高了25.11%。

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