Combined $\mathcal{L}_2$ -Stable Feedback and Feedforward Aeration Control in a Wastewater Treatment Plant

Chistiakova, Tatiana; Wigren, Torbjörn; Carlsson, Bengt

doi:10.1109/tcst.2019.2891410

Cited by 20 publications

(3 citation statements)

References 11 publications

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“…On the basis of meeting the above basic principles and without affecting the quality of early warning, the water quality indicators needed for early warning should be optimally reduced as much as possible in order to shorten the process time of early warning and improve the efficiency of early warning [18].…”

Section: Screening Principles Of Early Warning Indicatorsmentioning

confidence: 99%

Early Warning System for Urban Industrial Wastewater based on Remote Sensing Technology and Image Analysis

2023

WPPCP

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With the rapid development of economy, the scale of China's cities is expanding, and the discharge of urban industrial wastewater is also increasing, which has caused some pressure on urban wastewater treatment plants. In this paper, a method of early warning analysis of urban industrial wastewater based on remote sensing technology and image analysis technology is proposed based on the analysis of the current situation of industrial wastewater discharge. The method is used in the sewage early warning system can effectively improve the operational efficiency of sewage treatment plants and water quality monitoring capabilities. It provides a reference basis for enterprises to provide real-time monitoring data and formulate corresponding pollution treatment plans. In view of the industrial sewage pollution, this paper proposes a scheme to build an early warning system for urban industrial sewage based on remote sensing technology and image analysis technology. The system combines remote sensing images and field data to identify industrial wastewater pollution characteristics as the core objective, classify and identify pollutant molecules in images through multi-scale identification and classification algorithms, and use discriminative methods to make a comprehensive evaluation of this water quality model. The results show that the early warning system can accurately identify industrial wastewater pollutants.

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Section: Screening Principles Of Early Warning Indicatorsmentioning

confidence: 99%

Early Warning System for Urban Industrial Wastewater based on Remote Sensing Technology and Image Analysis

2023

WPPCP

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“…Thus, water output from these models is used for non-drinking purposes only. Inspired by these approaches the work in Harrou et al (2021) and Chistiakova et al (2020) propose designs of datadriven soft sensors (DDSSs), and feedback and feedforward aeration control (FFAC) models. These models have a general purpose, and utilize chemical composition for reducing impurities, thereby assisting in better quality of water, which can be used for human and animal use.…”

Section: Literature Reviewmentioning

confidence: 99%

Pragmatic analysis of wastewater treatment methods from a statistical perspective

Pande

Bhagat

2022

Water Practice and Technology

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Wastewater treatment is an environmental issue of utmost importance. Various models and architectures for wastewater treatment exist, each having its unique characteristics. In this study, an application-specific review of various treatment models is performed. Extensions to existing treatment models are discussed for improvement in process performance. The treatment models are compared statistically based on their performance metrics, namely the quality of treated water (Q), sludge percentage at output (SL), complexity of treatment (C), time needed for treatment (T), and deployment cost (DC). A novel parameter, model rank, is proposed that combines all the performance metrics into a single number so that the treatment models can be analyzed effectively. Results show that advanced oxidation processes with ozone treatment (AOPO), Kernel principal components analysis-based one-class support vector machine (KPCA SVM), electrochemical processes (EPs), membrane and absorption (MA), Nondominated Sorting Genetic Algorithm-based Optimal Controller (NSGAOC), and wet-type nonthermal plasma reactor (WTNPR) models have a rank above 3.5. The AOPO model has the highest model rank of 3.85 and thus has better overall performance than others. This study might aid major stakeholders in waste treatment industry including researchers in selecting the appropriate wastewater treatment method according to their requirements.

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“…Total nitrogen concentration is an important indicator to measure the quality of efuent water [1][2][3]. Excessive discharge of total nitrogen can cause serious consequences, such as reduced dissolved oxygen concentration in water bodies, eutrophication of water bodies, and death of organisms [4][5][6]. For this issue, China stipulates the daily maximum allowable emission concentration for basic control projects of water pollutant emissions ( Table 1, 2002).…”

Section: Introductionmentioning

confidence: 99%

Research on Optimization of Total Nitrogen Peak Suppression in Wastewater Treatment Based on the Data Driven Method

Lu,

Dong

2023

Journal of Control Science and Engineering

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In order to solve the problems of water eutrophication, algae anoxic decay, and death by biological poisoning, which are caused by the excessive emission of total nitrogen in wastewater treatment process, this paper proposes a method of total nitrogen peak suppression which is based on neural network decision optimization. First, the SSORBF neural network is established according to the wastewater treatment process, and total nitrogen, inflow flow, current total nitrogen, dissolved oxygen concentration, and nitrate nitrogen concentration are selected to predict the total nitrogen concentration. Second, the density- and memory-based NSGA2 multiobjective optimization method is used to set the optimal solution to meet the requirement of energy consumption. If the prediction of total nitrogen exceeded the set value, the optimal control strategy is adopted to control the peak value of total nitrogen in advance, and it cannot exceed the national maximum allowable emission value. If the prediction of total nitrogen is lower than the set value, it continues to track the parameter set value. Finally, compared with other methods, the proposed method can effectively suppress the peak value of total nitrogen under 18 mg/L and reduce the energy consumption in wastewater treatment by 7.6%. It can provide decisions and advice for wastewater treatment plants.

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Combined $\mathcal{L}_2$ -Stable Feedback and Feedforward Aeration Control in a Wastewater Treatment Plant

Cited by 20 publications

References 11 publications

Early Warning System for Urban Industrial Wastewater based on Remote Sensing Technology and Image Analysis

Early Warning System for Urban Industrial Wastewater based on Remote Sensing Technology and Image Analysis

Pragmatic analysis of wastewater treatment methods from a statistical perspective

Research on Optimization of Total Nitrogen Peak Suppression in Wastewater Treatment Based on the Data Driven Method

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