Multi-objective integrated optimal control for a wastewater treatment process

Han, Honggui; Chen, Cong; Sun, Haoyuan; Qiao, Junfei

doi:10.1016/j.conengprac.2022.105296

Cited by 10 publications

(3 citation statements)

References 33 publications

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“…Substituting equations ( 27) and ( 28) into equation (26), the weight update of W m o (t) can be written as…”

Section: The Design Of Lstm-based Modelingmentioning

confidence: 99%

“…Santı´n et al 25 proposed a fuzzy and MPC method by regulating the concentration of DO, NO, and so on, to eliminate effluent violations. Han et al 26 combined the MPC and multigradient algorithm, which improved the operation performance with satisfactory control accuracy. However, MPC is based on mathematical model, which is difficult to establish for WWTP.…”

Section: Introductionmentioning

confidence: 99%

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Long short-term memory-based modeling and controlling method for wastewater treatment process

Yang

She

Wu³

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part I:

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Considering the characteristics of large time variation, strong coupling, large time delay, and serious interference of wastewater treatment system, this article proposes an offline modeling and online controlling method based on long short-term memory network to improve multivariable control and prediction accuracy under disturbance. First, a prediction model of dissolved oxygen and nitrate nitrogen concentrations is established, and the stability of this long short-term memory-based modeling method is proven via the limitation of learning rate. Second, based on the prediction model, a multivariable long short-term memory-based controller is designed to improve the control accuracy by gradient descent algorithm, and the stability of the long short-term memory-based controller is proved by Lyapunov principle. Finally, based on the Benchmark Simulation Model No.1, the simulation experiments of long short-term memory-based modeling and controlling method, the default proportion–integration control method (proposed in the Benchmark Simulation Model No.1), and model predictive control method are conducted and compared, respectively. The results show the long short-term memory-based method owns both better approximating and controlling performance, and compared with the default proportion–integration and model predictive control, the long short-term memory-based controller reduces the integral squared error of dissolved oxygen and nitrate nitrogen concentrations by more than 94% and 80%, respectively.

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“…Substituting equations ( 27) and ( 28) into equation (26), the weight update of W m o (t) can be written as…”

Section: The Design Of Lstm-based Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Long short-term memory-based modeling and controlling method for wastewater treatment process

Yang

She

Wu³

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part I:

View full text Add to dashboard Cite

show abstract

“…In addition, device manufacturers are trying to provide better, optimized devices [ 21 , 22 ], ensuring long-term operation and resistance to typical hazards in this work environment [ 18 ]. Advanced control algorithms are also being developed, from the level of individual devices and their groups, to the complex control of the SCADA process at a high level—overall control of all sewage treatment processes [ 23 ]. Various modeling methods and combining theoretical models with real devices as a digital twin are also being developed [ 12 , 24 , 25 ].…”

Section: Introductionmentioning

confidence: 99%

Condition-Based Failure-Free Time Estimation of a Pump

Ćwikła

Paprocka

2023

Sensors

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Reliable and continuous operation of the equipment is expected in the wastewater treatment plant, as any perturbations can lead to environmental pollution and the need to pay penalties. Optimization and minimization of operating costs of the pump station cannot, therefore, lead to a reduction in reliability but rather should be based on preventive works, the necessity of which should be foreseen. The purpose of this paper is to develop an accurate model to predict a pump’s mean time to failure, allowing for rational planning of maintenance. The pumps operate under the supervision of the automatic control system and SCADA, which is the source of historical data on pump operation parameters. This enables the research and development of various methods and algorithms for optimizing service activities. In this case, a multiple linear regression model is developed to describe the impact of historical data on pump operation for pump maintenance. In the literature, the least squares method is used to estimate unknown regression coefficients for this data. The original value of the paper is the application of the genetic algorithm to estimate coefficient values of the multiple linear regression model of failure-free time of the pump. Necessary analysis and simulations are performed on the data collected for submersible pumps in a sewage pumping station. As a result, an improvement in the adequacy of the presented model was identified.

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Data-driven modeling and stability control for industrial zinc roaster and its edge controller implementation

Ying

Huang

et al. 2023

Control Engineering Practice

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Multi-objective integrated optimal control for a wastewater treatment process

Cited by 10 publications

References 33 publications

Long short-term memory-based modeling and controlling method for wastewater treatment process

Long short-term memory-based modeling and controlling method for wastewater treatment process

Condition-Based Failure-Free Time Estimation of a Pump

Data-driven modeling and stability control for industrial zinc roaster and its edge controller implementation

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