Paper Info
Title
Optimal control for wastewater treatment process based on an adaptive multi-objective differential evolution algorithm
Abstract
In this paper, for the operations of wastewater treatment processes (WWTPs), an intelligent multi-objective optimization control (IMOOC), based on an adaptive multi-objective differential evolution (AMODE) algorithm, is proposed to search for the suitable set-points to balance the treatment performance and the operational costs. In this IMOOC, the combination of an AMODE algorithm and the multi-objective critical issues helps us to fulfill all the control objectives simultaneously. To improve the optimization efficiency and achieve fast convergence, the AMODE algorithm is designed to improve the local search and the global exploration abilities: The adaptive adjustment strategies are developed to select the suitable scaling factor and crossover rate in the process of searching. Meanwhile, the multi-objective critical issues, according to the state of the processes, are given as a nonlinear multi-objective optimization problem to evaluate the operational performance of WWTPs. Therefore, once the nonlinear multi-objective optimization problem is solved at each sampling time, the most appropriate set of Pareto is selected as suitable set-points to achieve the process performance. To demonstrate the merits of our proposed method, the proposed IMOOC is applied to the Benchmark Simulation Model No. 1 of WWTPs. The results show that the proposed IMOOC effectively provides process control. The performance comparison with other algorithms also indicates that the proposed optimal strategy yields better effluent qualities and lower average operation consumption.
Year
DOI
Venue
2019
10.1007/s00521-017-3212-4
Neural Computing and Applications
Keywords
Field
DocType
Intelligent multi-objective optimization control, Adaptive multi-objective differential evolution, Wastewater treatment processes, Optimal strategy
Convergence (routing),Mathematical optimization,Optimal control,Nonlinear system,Differential evolution,Process control,Local search (optimization),Optimization problem,Mathematics,Pareto principle
Journal
Volume
Issue
ISSN
31.0
7
1433-3058
Citations 
PageRank 
References 
0
0.34
11
Authors
3
Name
Order
Citations
PageRank
Junfei Qiao121.38
Ying Hou2403.43
Hong-Gui Han347639.06