Artificial Neural Networks Modelling of PID and Model Predictive Controlled Waste Water Treatment Plant Based on the Benchmark Simulation Model No.1

Vasile Mircea Cristea; Cristian Pop; Paul Serban Agachi

doi:10.1016/S1570-7946(09)70197-X

Artificial Neural Networks Modelling of PID and Model Predictive Controlled Waste Water Treatment Plant Based on the Benchmark Simulation Model No.1

Vasile Mircea Cristea
, Cristian Pop
, Paul Serban Agachi

Chemical, Materials & Metallurgical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Chapter

6 Citations (Scopus)

Abstract

The paper presents techniques for the design and training of Artificial Neural Networks (ANN) models for the dynamic simulation of the controlled Benchmark Simulation Model no. 1 (BSM1) Waste Water Treatment Plant (WWTP). The developed ANN model of the WWTP and its associated control system is used for the assessment of the plant behaviour in integrated urban waste water system simulations. Both embedded PID (Proportional-Integral-Derivative) control and Model Predictive Control (MPC) structures for the WWTP are investigated. The control of the Dissolved Oxygen (DO) mass concentration in the aerated reactors and nitrate (NO) mass concentration in the anoxic compartments are presented. The ANN based simulators reveal good accuracy for predicting important process variables and an important reduction of the simulation time, compared to the first principle WWTP simulator.

Original language	English
Title of host publication	19th European Symposium on Computer Aided Process Engineering
Editors	Jacek Jezowski, Jan Thullie
Pages	1183-1188
Number of pages	6
DOIs	https://doi.org/10.1016/S1570-7946(09)70197-X
Publication status	Published - 2009

Publication series

Name	Computer Aided Chemical Engineering
Volume	26
ISSN (Print)	1570-7946

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

All Science Journal Classification (ASJC) codes

General Chemical Engineering
Computer Science Applications

Access to Document

10.1016/S1570-7946(09)70197-X

Cite this

Cristea, V. M., Pop, C., & Serban Agachi, P. (2009). Artificial Neural Networks Modelling of PID and Model Predictive Controlled Waste Water Treatment Plant Based on the Benchmark Simulation Model No.1. In J. Jezowski, & J. Thullie (Eds.), 19th European Symposium on Computer Aided Process Engineering (pp. 1183-1188). (Computer Aided Chemical Engineering; Vol. 26). https://doi.org/10.1016/S1570-7946(09)70197-X

Cristea, Vasile Mircea ; Pop, Cristian ; Serban Agachi, Paul. / Artificial Neural Networks Modelling of PID and Model Predictive Controlled Waste Water Treatment Plant Based on the Benchmark Simulation Model No.1. 19th European Symposium on Computer Aided Process Engineering. editor / Jacek Jezowski ; Jan Thullie. 2009. pp. 1183-1188 (Computer Aided Chemical Engineering).

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title = "Artificial Neural Networks Modelling of PID and Model Predictive Controlled Waste Water Treatment Plant Based on the Benchmark Simulation Model No.1",

abstract = "The paper presents techniques for the design and training of Artificial Neural Networks (ANN) models for the dynamic simulation of the controlled Benchmark Simulation Model no. 1 (BSM1) Waste Water Treatment Plant (WWTP). The developed ANN model of the WWTP and its associated control system is used for the assessment of the plant behaviour in integrated urban waste water system simulations. Both embedded PID (Proportional-Integral-Derivative) control and Model Predictive Control (MPC) structures for the WWTP are investigated. The control of the Dissolved Oxygen (DO) mass concentration in the aerated reactors and nitrate (NO) mass concentration in the anoxic compartments are presented. The ANN based simulators reveal good accuracy for predicting important process variables and an important reduction of the simulation time, compared to the first principle WWTP simulator.",

author = "Cristea, \{Vasile Mircea\} and Cristian Pop and \{Serban Agachi\}, Paul",

year = "2009",

doi = "10.1016/S1570-7946(09)70197-X",

language = "English",

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booktitle = "19th European Symposium on Computer Aided Process Engineering",

}

Cristea, VM, Pop, C & Serban Agachi, P 2009, Artificial Neural Networks Modelling of PID and Model Predictive Controlled Waste Water Treatment Plant Based on the Benchmark Simulation Model No.1. in J Jezowski & J Thullie (eds), 19th European Symposium on Computer Aided Process Engineering. Computer Aided Chemical Engineering, vol. 26, pp. 1183-1188. https://doi.org/10.1016/S1570-7946(09)70197-X

Artificial Neural Networks Modelling of PID and Model Predictive Controlled Waste Water Treatment Plant Based on the Benchmark Simulation Model No.1. / Cristea, Vasile Mircea; Pop, Cristian; Serban Agachi, Paul.
19th European Symposium on Computer Aided Process Engineering. ed. / Jacek Jezowski; Jan Thullie. 2009. p. 1183-1188 (Computer Aided Chemical Engineering; Vol. 26).

Research output: Chapter in Book/Report/Conference proceeding › Chapter

TY - CHAP

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AU - Pop, Cristian

AU - Serban Agachi, Paul

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Y1 - 2009

N2 - The paper presents techniques for the design and training of Artificial Neural Networks (ANN) models for the dynamic simulation of the controlled Benchmark Simulation Model no. 1 (BSM1) Waste Water Treatment Plant (WWTP). The developed ANN model of the WWTP and its associated control system is used for the assessment of the plant behaviour in integrated urban waste water system simulations. Both embedded PID (Proportional-Integral-Derivative) control and Model Predictive Control (MPC) structures for the WWTP are investigated. The control of the Dissolved Oxygen (DO) mass concentration in the aerated reactors and nitrate (NO) mass concentration in the anoxic compartments are presented. The ANN based simulators reveal good accuracy for predicting important process variables and an important reduction of the simulation time, compared to the first principle WWTP simulator.

AB - The paper presents techniques for the design and training of Artificial Neural Networks (ANN) models for the dynamic simulation of the controlled Benchmark Simulation Model no. 1 (BSM1) Waste Water Treatment Plant (WWTP). The developed ANN model of the WWTP and its associated control system is used for the assessment of the plant behaviour in integrated urban waste water system simulations. Both embedded PID (Proportional-Integral-Derivative) control and Model Predictive Control (MPC) structures for the WWTP are investigated. The control of the Dissolved Oxygen (DO) mass concentration in the aerated reactors and nitrate (NO) mass concentration in the anoxic compartments are presented. The ANN based simulators reveal good accuracy for predicting important process variables and an important reduction of the simulation time, compared to the first principle WWTP simulator.

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M3 - Chapter

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T3 - Computer Aided Chemical Engineering

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BT - 19th European Symposium on Computer Aided Process Engineering

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Cristea VM, Pop C, Serban Agachi P. Artificial Neural Networks Modelling of PID and Model Predictive Controlled Waste Water Treatment Plant Based on the Benchmark Simulation Model No.1. In Jezowski J, Thullie J, editors, 19th European Symposium on Computer Aided Process Engineering. 2009. p. 1183-1188. (Computer Aided Chemical Engineering). doi: 10.1016/S1570-7946(09)70197-X

Artificial Neural Networks Modelling of PID and Model Predictive Controlled Waste Water Treatment Plant Based on the Benchmark Simulation Model No.1

Abstract

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