A stochastic approach for the solution of single and multi–objective optimisation problems of biological processes in sequencing batch reactor

IF 3.3 2区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Journal of Process Control Pub Date : 2024-06-20 DOI:10.1016/j.jprocont.2024.103266

Tomasz Ujazdowski, Robert Piotrowski, Michał Banach

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Abstract

This paper investigates the impact of implementing single and multi-optimisation solutions on the biological treatment process in a sequencing batch reactor (SBR). The research is based on a case study of the water resource recovery facility (WRRF) in Swarzewo, Northern Poland. The paper introduces the adaptive extremum seeking control (ESC) method for dissolved oxygen (DO) concentration control and places it in a layered control structure. Further, it presents the introduction of an optimisation layer for the structure and parameters of the SBR cycle, through the synthesis of stochastic methods: single-objective optimisation (SOO) using a genetic algorithm (GA) and multi-objective optimisation (MOO) using the NSGA-II algorithm. The results were compared to a classical approach with fixed cycle parameters. The paper shows the advantages of optimising cycle parameters, including the number of phases as well as the DO value, on the process flow. These control structures underwent simulation tests in the MATLAB environment with the Simba package. The biochemical processes occurring in the reactor are based on the Activated Sludge Model No. 2d (ASM2d). The optimising control system demonstrates tangible improvements in operational efficiency and significant reductions in electrical energy consumption, highlighting the effectiveness of the proposed methodologies. © 2017 Elsevier Inc. All rights reserved.

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解决序批式反应器中生物过程的单目标和多目标优化问题的随机方法

本文研究了在序批式反应器（SBR）中实施单一和多重优化方案对生物处理过程的影响。研究以波兰北部斯瓦泽沃的水资源回收设施（WRRF）为案例。论文介绍了用于溶解氧（DO）浓度控制的自适应极值寻求控制（ESC）方法，并将其置于分层控制结构中。此外，论文还介绍了通过综合使用随机方法，为 SBR 循环的结构和参数引入优化层：使用遗传算法 (GA) 的单目标优化 (SOO) 和使用 NSGA-II 算法的多目标优化 (MOO)。结果与采用固定循环参数的传统方法进行了比较。论文显示了优化周期参数（包括阶段数和 DO 值）对工艺流程的优势。这些控制结构在 MATLAB 环境中使用 Simba 软件包进行了模拟测试。反应器中的生化过程基于活性污泥模型 2d (ASM2d)。优化控制系统切实提高了运行效率，大幅降低了电能消耗，凸显了建议方法的有效性。© 2017 Elsevier Inc.保留所有权利。

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来源期刊

Journal of Process Control 工程技术-工程：化工

CiteScore

7.00

自引率

11.90%

发文量

159

审稿时长

74 days

期刊介绍： This international journal covers the application of control theory, operations research, computer science and engineering principles to the solution of process control problems. In addition to the traditional chemical processing and manufacturing applications, the scope of process control problems involves a wide range of applications that includes energy processes, nano-technology, systems biology, bio-medical engineering, pharmaceutical processing technology, energy storage and conversion, smart grid, and data analytics among others. Papers on the theory in these areas will also be accepted provided the theoretical contribution is aimed at the application and the development of process control techniques. Topics covered include: • Control applications• Process monitoring• Plant-wide control• Process control systems• Control techniques and algorithms• Process modelling and simulation• Design methods Advanced design methods exclude well established and widely studied traditional design techniques such as PID tuning and its many variants. Applications in fields such as control of automotive engines, machinery and robotics are not deemed suitable unless a clear motivation for the relevance to process control is provided.