In this article, we consider state estimation of wastewater treatment plants based on model approximation. In particular, we consider a wastewater treatment plant described by the Benchmark Simulation Model No.1 which consists of a five-chamber reactor and a settler. We propose to use the proper orthogonal decomposition approach with re-identification of output equations to obtain a reduced-order model of the original system. Then, the reduced-order model is taken advantage of in state estimation. An approach on how to determine an appropriate minimum measurement set is also proposed based on degree of observability. A continuous-discrete extended Kalman filtering algorithm is used to design the estimator based on the reduced-order model. We show through extensive simulations under different weather conditions that the estimator based on the reduced-order model with re-identified output equations gives good state estimates of the actual process.

在本文中，我们考虑基于模型逼近的污水处理厂状态估算。特别是，我们考虑了基准模拟模型No.1所描述的废水处理厂，该厂由一个五室反应器和一个沉降器组成。我们建议使用适当的正交分解方法对输出方程进行重新识别，以获得原始系统的降阶模型。然后，在状态估计中利用降阶模型。还基于可观察性的程度，提出了一种如何确定适当的最小测量集的方法。基于降阶模型，采用连续离散扩展卡尔曼滤波算法设计估计量。