污水处理过程聚类多模型建模与应用

Multi-model modeling for wastewater treatment system based on clustering analysis and its application

针对污水生化处理过程单模型建模存在计算量大和精度差等的问题,提出一种改进的有监督的k-means聚类算法的ARX多模型建模方法。该方法引入CCIA算法初始化聚类中心的思想,对样本数据进行聚类及二次聚类划分,并对各类数据分别建立ARX子模型,系统模型通过子模型加权合成。将该方法应用于污水处理过程中氨氮浓度模型辨识,仿真结果和实际污水处理厂实践结果表明,该建模方法具有较高的精度,能准确拟合系统的非线性特性。

Abstract： For wastewater treatment processes, a single model suffers from heavy burden calculation and bad accuracy. A mod- eling method based on ARX （auto-regressive exogenous） multi-model using improved supervised k-means clustering algorithm is proposed. The method introduced the cluster center initialization idea of CCIA algorithm into classical k-means clustering algorithm applied to group the data into clusters or second clustering by judging a preset threshold value, and the least squares method is used to construct ARX sub-models. The system model is constructed by weighting all ARX sub-models. The proposed method is used to identify the ammonia concentration model for wastewater treatment system. Simulation and practice results show that the proposed method can be used to fit nonlinear characteristics o＇f the system with high precision.