基于改进布谷鸟搜索算法的活性污泥工艺参数估计。

Parameter estimation of activated sludge process based on an improved cuckoo search algorithm.

机构信息

College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China; School of Engineering, RMIT University, Melbourne 3000, Australia; Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou University of Technology, Lanzhou 730050, China; National Demonstration Center for Experimental Electrical and Control Engineering Education, Lanzhou University of Technology, Lanzhou 730050, China.

College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China; Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou University of Technology, Lanzhou 730050, China; National Demonstration Center for Experimental Electrical and Control Engineering Education, Lanzhou University of Technology, Lanzhou 730050, China.

出版信息

Bioresour Technol. 2018 Feb;249:447-456. doi: 10.1016/j.biortech.2017.10.023. Epub 2017 Oct 10.

DOI:10.1016/j.biortech.2017.10.023

PMID:29065327

Abstract

It is essential to use appropriate values for kinetic parameters in activated sludge model when the model is applied for wastewater treatment processes under different environments. An improved cuckoo search (ICS) algorithm was proposed in this paper for the estimation of kinetic parameters used in Activated Sludge Model No. 1 (ASM1). ICS is tested for its speed and accuracy in reaching solution by searching global minima of six standard functions. Cyclical adjustment strategy was employed into the detected probability to increase searching ability. Meanwhile, the searching step was adaptively adjusted based on the optimal nest of the last generation and the current iteration numbers. Subsequently, ICS is used to estimate 7 sensitive parameters in ASM1 for practical applications. Field data are used to validate prediction accuracy of ASM1 with estimated parameters. Predicted results of the model are closer to the actual data with adjusted parameters.

摘要

在应用活性污泥模型（ASM1）于不同环境下的废水处理工艺时，为了使模型能够准确模拟，为动力学参数赋值十分关键。本文提出了一种改进的布谷鸟搜索（ICS）算法，用于估计活性污泥模型中的动力学参数。ICS 通过搜索六个标准函数的全局最小值来测试其寻找解决方案的速度和准确性。循环调整策略被应用于检测概率中，以提高搜索能力。同时，根据上一代最优鸟巢和当前迭代次数自适应调整搜索步长。随后，ICS 被用于估计 ASM1 中的 7 个敏感参数，以进行实际应用。使用现场数据验证了具有估计参数的 ASM1 的预测精度。调整参数后的模型预测结果与实际数据更加吻合。