兰州理工大学学报

兰州理工大学学报 ›› 2020, Vol. 46 ›› Issue (1): 93-99.

• 自动化技术与计算机技术 • 上一篇    下一篇

基于改进多目标布谷鸟算法的污水处理优化控制方法

赵小强1,2,3, 李丽娟1, 冯小林1,2,3   

  1. 1.兰州理工大学 电气工程与信息工程学院, 甘肃 兰州 730050;
    2.兰州理工大学 甘肃省工业过程先进控制重点实验室, 甘肃 兰州 730050;
    3.兰州理工大学 国家级电气与控制工程实验教学中心, 甘肃 兰州 730050
  • 收稿日期:2018-05-16 出版日期:2020-02-28 发布日期:2020-06-23
  • 作者简介:赵小强(1969-),男,陕西岐山人,博士,教授,博导.
  • 基金资助:
    国家自然科学基金(61763029),大型电气传动系统与装备技术国家重点实验室开放基金(SKLLDJ012016020

Optimizing control method for sewage treatment based on improved multi-objective cuckoo algorithm

ZHAO Xiao-qiang1,2,3, LI Li-juan1, FENG Xiao-lin1,2,3   

  1. 1. College of Electrical and Information Engineering, Lanzhou Univ. of Tech. , Lanzhou 730050, China;
    2. Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou Univ. of Tech. , Lanzhou 730050, China;
    3. National Experimental Teaching Center of Electrical and Control Engineering, Lanzhou Univ. of Tech. , Lanzhou 730050, China
  • Received:2018-05-16 Online:2020-02-28 Published:2020-06-23

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摘要： 针对如何确定污水处理优化控制中关键变量的最优设定值,以满足出水水质达标的同时尽可能降低能耗的问题,提出一种基于改进多目标布谷鸟算法的污水处理多目标优化控制方法.首先,通过对污水处理过程的分析,建立基于神经网络的污水处理能耗和出水水质模型;其次,利用改进多目标布谷鸟算法同时对污水处理能耗和出水水质模型进行优化,得到溶解氧和硝态氮浓度的优化设定值;最后,利用PID控制器对关键变量的最优设定值进行跟踪控制,实现污水处理过程的多目标优化控制.仿真实验结果表明,与其他几种方法相比,所提出的方法在保证出水水质参数达标的前提下,更好地降低了污水处理过程的能耗,实现节能降耗和保护环境的目的.

关键词: 污水处理, 优化控制, 基准仿真模型, 多目标布谷鸟算法

Abstract: Aimed at the problems such as how to determine the optimal setting value of key variables in the process of optimizing control of wastewater treatment process (WWTP) to achieve the standard of effluent water quality and at the same time toreduce the energy consumption (EC) as much as possible, a multi-objective optimizing control method is proposed based on improved multi-objective cuckoo search algorithm (IMOCS). First, theEC and EQ models are presented based on neural network and analysis of wastewater treatment process. Then, both the EC and EQ models are simultaneously optimized by means of improved multi-objective cuckoo search algorithm and the optimal setting values of concentration of dissolved oxygen(DO) and nitrate-level nitrogen are obtained. Finally, the PID controller is chosen to conduct the tracing control of the optimal setting value, so that the multi-objective optimizing control of WWTP is achieved. Based on the international benchmark simulation platform No.1, and compared with other methods, it is shown that the proposed method can reduce EQ better in the process of sewage treatment and protect the environment, going on the premise of assuring the achievement of standard of the parameters of effluent water quality.

Key words: sewage treatment, optimizing control, benchmark simulation model, multi-objective cuckoo search algorithm

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