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Inicio Revista Iberoamericana de Automática e Informática Industrial RIAI Control en Estaciones Depuradoras de Aguas Residuales: Estado actual y perspecti...
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Vol. 14. Núm. 4.
Páginas 329-345 (octubre - diciembre 2017)
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Vol. 14. Núm. 4.
Páginas 329-345 (octubre - diciembre 2017)
Open Access
Control en Estaciones Depuradoras de Aguas Residuales: Estado actual y perspectivas
Control and operation of wastewater treatment plants: challenges and state of the art
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5436
Ramon Vilanova
Autor para correspondencia
Ramon.Vilanova@uab.cat

Autor para correspondencia.
, Ignacio Santín, Carles Pedret
Departamento de Telecomunicaciones y de Ingeniería de Sistemas, Escuela de Ingeniería, Universidad Autónoma de Barcelona, 08193 Bellaterra, Barcelona, Spain
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Este trabajo constituye la segunda parte de una revisión de la problemática del control de estaciones depuradoras de aguas residuales (EDAR) para el tratamiento de agua residual urbana. Después de haber presentado en la primera parte las perspectivas correspondientes al modelado y simulación, en esta segunda parte nos centramos en el control de las mismas. Esta depuración se realiza, mayoritariamente, mediante procesos biológicos, concretamente, mediante el denominado proceso de fangos activados. El hecho de tratar con un proceso biológico conlleva una elevada complejidad tanto desde el punto de vista de modelado como, por supuesto, de control. Se revisa el control de EDAR desde su perspectiva histórica, como de los lazos de control más usuales, problemáticas que presentan y algunas de las soluciones propuestas. Se realiza también una revisión de la aplicación de las diferentes técnicas de control catalogándolas de acuerdo a su filosofía. Para terminar se ofrece una visión de las tendencia actuales y perspectivas de desarrollos futuros.

Palabras clave:
Estaciones depuradoras de aguas residuales
benchmarking
control y operación
Abstract

This tutorial is the second part of a review of the problems arising with the control and operation of wastewater treatment plants (WWTP) for urban wastewater. Having presented in the first part the modelling and simulation steps, in this second part we cover the control and operation issues. This treatment is carried out, mainly, by biological processes, specifically, by the so-called activated sludge process. Dealing with a biological process entails a high complexity both from the viewpoint of modelling and, of course, from what matters to control and operation. The control of WWTP is reviewed from an historical perspective, as well as the most common control loops, the problems that present and some of the proposed solutions. A review of the applications of different control techniques is also cataloged according to the philosophy of the control approach. Finally, it offers an overview of the current trends and future development prospects.

Keywords:
wastewater treatment plants benchmarking control and operation
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Achleitner et al., 2007, Åmand and Carlsson, 2012, Astaraie-Imani et al., 2012, Baeza et al., 1999, Baeza et al., 2002, Baeza et al., 2004, Barbu et al., 2017, Barnett and Andrews, 1990, Baruch et al., 2004, Bastin and Dochain, 1990, Belchior et al., 2011, Benedetti et al., 2010, Beraud et al., 2009, Biswas et al., 2007, Bracken and Flanagan, 1977, Brdys et al., 2008, Brdys and Konarzcak, 2001, Brdys and Maíquez, 2002, Bridle et al., 2008, Butler and Schutze, 2005, Chen and Pham, 2000, Chotkowski et al., 2005, Copp, 2002, Corominas et al., 2013, Cristea et al., 2011, Dapena-Mora et al., 2004, Desloover et al., 2012, Doby et al., 2002, Dochain, 1991, Dochain and Perrier, 1993, Doglioni et al., 2009, Ekman et al., 2006, Flores-Alsina et al., 2014, Flores-Alsina et al., 2011, Flores-Alsina et al., 2008, Francisco et al., 2015, Fu and Butler, 2012, Fu et al., 2010, Gernaey and Jørgensen, 2004, Güçlü and Dursun, 2010, Guerrero et al., 2012, Guo et al., 2012, Han et al., 2008, Henze et al., 2002, Hiatt and Grady, 2008, Holenda et al., 2008, IFAK, 2007, Ingildsen, 2002, Ingildsen et al., 2002, Jager, 1995, Jeppsson et al., 2013, Kabouris and Georgakakos, 1990, Kabouris et al., 1992, Kampschreur et al., 2008, Krause et al., 2002a, Krause et al., 2002b, Lijklema et al., 1993, Lindberg and Carlsson, 1996a, Lindberg and Carlsson, 1996b, Lingireddy and Brion, 2005, Lukasse et al., 1998, Lukasse et al., 1999, Lukasse et al., 1997, Lynggaard-Jensen et al., 2010, Machado et al., 2009, Maeda et al., 1990, Maere et al., 2011, Marsili-Libelli, 1984, Marsili-Libelli, 1989, Meirlaen et al., 2002, Meneses et al., 2016, Meneses et al., 2015, Meyer and Pöpel, 2003, Nasr et al., 2014, Ni et al., 2012, Olsson et al., 1989, Olsson et al., 1998, Olsson and Newell, 1999, Olsson et al., 2005, Olsson et al., 1985, Ostace et al., 2013, Pan et al., 2013, Peng et al., 2005, Piotrowski et al., 2008, Rauch et al., 2002, Rauch, 1999, Revollar et al., 2015, Rieger et al., 2003, Rodriguez-Roda et al., 2002, Rojas et al., 2011, Rojas et al., 2012, Rossman, 2009, Samie et al., 2011, Samuelsson and Carlsson, 2001, Samuelsson et al., 2007, Santín et al., 2015a, Santín et al., 2015b, Santiń et al., 2016a, Santiń et al., 2016b, Schmitt and Huber, 2006, Schutze et al., 2011, Schutze et al., 1999, Serralta et al., 2002, Shanahan et al., 2001, Shen et al., 2009, Singman, 1999, Stare et al., 2007a, Stare et al., 2007b, Steffens and Lant, 1999, Stephanopoulos and Ng, 2000, Stepner and Petersack, 1974, Steyer et al., 2006, Traoré et al., 2006, Vanrolleghem, 1994, Vanrolleghem et al., 2004, Vanrolleghem and Gillot, 2002a, Vanrolleghem and Gillot, 2002b, Vanrolleghem et al., 1996, Vilanova and Alfaro, 2011, Vilanova et al., 2009, Vilanova et al., 2011, Vilanova et al., 2017, Vitasovic and Andrews, 1989, Vrečko et al., 2006, Vrečko et al., 2011, Wahab and Katebi, 2009, Yamanaka et al., 2006, Yong et al., 2006a, Yong et al., 2006b, Yuan and Blackall, 2002, Yuan et al., 2002a, Yuan and Keller, 2003, Yuan et al., 2002b, Zhao and Chai, 2005 and Zhu et al., 2009.

Referencias
[Achleitner et al., 2007]
S. Achleitner, M. Moderl, W. Rauch.
CITY DRAIN © – an open source approach for simulation of integrated urban drainage systems.
Environmental Modelling & Software, 22 (2007 aug), pp. 1184-1195
[Åmand and Carlsson, 2012]
L. Åmand, B. Carlsson.
Optimal aeration control in a nitrifying activated sludge process.
Water Research, 46 (2012 may), pp. 2101-2110
[Astaraie-Imani et al., 2012]
M. Astaraie-Imani, Z. Kapelan, G. Fu, D. Butler.
Assessing the combined effects of urbanisation and climate change on the river water quality in an integrated urban wastewater system in the UK.
Journal of Environmental Management, 112 (2012 dec), pp. 1-9
[Baeza et al., 1999]
J. Baeza, D. Gabriel, J. Lafuente.
An expert supervisory system for a pilot WWTP.
Environmental Modelling & Software, 14 (1999 mar), pp. 383-390
[Baeza et al., 2002]
J. Baeza, D. Gabriel, J. Lafuente.
Improving the nitrogen removal efficiency of an a2/o based WWTP by using an on-line knowledge based expert system.
Water Research, 36 (2002 apr), pp. 2109-2123
[Baeza et al., 2004]
J. Baeza, D. Gabriel, J. Lafuente.
Effect of internal recycle on the nitrogen removal efficiency of an anaerobic/anoxic/oxic (a2/o) wastewater treatment plant (WWTP).
Process Biochemistry, 39 (2004 jul), pp. 1615-1624
[Barbu et al., 2017]
M. Barbu, R. Vilanova, M. Meneses, I. Santin.
On the evaluation of the global impact of control strategies applied to wastewater treatment plants.
Journal of Cleaner Production, 149 (2017), pp. 396-405
[Barnett and Andrews, 1990]
M.W. Barnett, J.F. Andrews.
Knowledge based systems for operation of wastewater treatment processes.
En: Instrumentation, Control and Automation of Water and Wastewater Treatment and Transport Systems, Elsevier, (1990), pp. 211-218
10.1016/b978-0-08-040776-0.50029-9
[Baruch et al., 2004]
I.S. Baruch, P. Georgieva, J. Barrera-Cortes, S.F. de Azevedo.
Adaptive recurrent neural network control of biological wastewater treatment.
International Journal of Intelligent Systems, 20 (2004), pp. 173-193
[Bastin and Dochain, 1990]
G. Bastin, D. Dochain.
On-line Estimation and Adaptive Control of Bioreactors.
Elsevier Science, (1990),
(Process Measurement and Control)
[Belchior et al., 2011]
C.A.C. Belchior, R.A.M. Araujo, J.A.C. Landeckb.
Dissolved oxygen control of the activated sludge wastewater treatment process using stable adaptive fuzzy control.
Computer and Chemical Engineering, 37 (2011), pp. 152-162
[Benedetti et al., 2010]
L. Benedetti, B. De Baets, I. Nopens, P.A. Vanrolleghem.
Multicriteria analysis of wastewater treatment plant design and control scenarios under uncertainty.
Environmental modelling & software, 25 (2010), pp. 616-621
[Beraud et al., 2009]
B. Beraud, C. Lemoine, J.-P. Steyer.
Multiobjective genetic algorithms for the optimisation of wastewater treatment processes.
En: Computational Intelligence Techniques for Bioprocess Modelling, Supervision and Control, Springer Nature, (2009), pp. 163-195
[Biswas et al., 2007]
P. Biswas, P. Bose, V. Tare.
Optimal choice of wastewater treatment train by multi-objective optimization.
Engineering Optimization, 39 (2007), pp. 125-145
[Bracken and Flanagan, 1977]
B. Bracken, M. Flanagan.
Design recommendations for automatic dissolved oxygen control.
Prog. Wat. Tech., 9 (1977), pp. 551-555
[Brdys et al., 2008]
M. Brdys, M. Grochowski, T. Gminski, K. Konarczak, M. Drewa.
Hierarchical predictive control of integrated wastewater treatment systems.
Control Engineering Practice, 16 (2008), pp. 751-767
[Brdys and Konarzcak, 2001]
M. Brdys, K. Konarzcak.
Dissolved oxygen control for activated sludge processes.
En: Proc. of the 9th IFAC/IFORS/IMACS/IFIP Symposium on Large Scale Systems: Theory Applications, Bucharest, (2001 18-20 July),
[Brdys and Maíquez, 2002]
M. Brdys, J.D. Maíquez.
Application of fuzzy model predictive control to the dissolved oxygen concentration tracking in an activated sludge process.
IFAC Proceedings Volumes, 35 (2002), pp. 35-40
[Bridle et al., 2008]
T. Bridle, A.C.S.Y.K.C.T.K. Shaw, M. Domurad.
Estimation of greenhouse gas emissions from wastewater treatment plants.
En: In Proceedings of the IWA World Water Congress, Austria, (2008 September 7-12), pp. 2008
[Butler and Schutze, 2005]
D. Butler, M. Schutze.
Integrating simulation models with a view to optimal control of urban wastewater systems.
Environmental Modelling & Software, 20 (2005), pp. 415-426
[Chen and Pham, 2000]
G. Chen, T.T. Pham.
Introduction to Fuzzy Sets, Fuzzy Logic, and Fuzzy Control Systems.
CRC Press, Boca Raton, (2000),
[Chotkowski et al., 2005]
W. Chotkowski, M.A. Brdys*, K. Konarczak.
Dissolved oxygen control for activated sludge processes.
International Journal of Systems Science, 36 (2005), pp. 727-736
[Copp, 2002]
J.B. Copp.
The Cost Simulation benchmark: Description and simulator manual.
Office for Official Publications od the European Union, (2002),
(COST Action 624 and Action 682)
[Corominas et al., 2013]
L. Corominas, J. Foley, J. Guest, A. Hospido, H. Larsen, S. Morera, A. Shaw.
Life cycle assessment applied to wastewater treatment: State of the art.
Water Research, 47 (2013 oct), pp. 5480-5492
[Cristea et al., 2011]
S. Cristea, C. de Prada, D. Sarabia, G. Gutierez.
Aeration control of a wastewater treatment plant using hybrid NMPC.
Computers & Chemical Engineering, 35 (2011), pp. 638-650
URL: https://doi.org/10.1016/j.compchemeng.2010.07.021
[Dapena-Mora et al., 2004]
A. Dapena-Mora, S.W.V. Hulle, J.L. Campos, R. Méndez, P.A. Vanrolleghem, M. Jetten.
Enrichment of anammox biomass from municipal activated sludge: experimental and modelling results.
Journal of Chemical Technology & Biotechnology, 79 (2004 oct), pp. 1421-1428
[Desloover et al., 2012]
J. Desloover, S.E. Vlaeminck, P. Clauwaert, W. Verstraete, N. Boon.
Strategies to mitigate n2o emissions from biological nitrogen removal systems.
Current Opinion in Biotechnology, 23 (2012 jun), pp. 474-482
[Doby et al., 2002]
T. Doby, D. Loughlin, F. De los Reyes, J. Ducoste.
Optimization of activated sludge designs using genetic algorithms.
Water science and technology, 45 (2002), pp. 187-198
[Dochain, 1991]
D. Dochain.
Design of adaptive controllers for non-linear stirred tank bioreactors: extension to the mimo situation.
Journal of Process Control, 1 (1991), pp. 41-48
[Dochain and Perrier, 1993]
D. Dochain, M. Perrier.
Control design for nonlinear wastewater treatment processes.
Water Science and Technology, 28 (1993), pp. 283-293
[Doglioni et al., 2009]
A. Doglioni, F. Primativo, D. Laucelli, V. Monno, S.-T. Khu, O. Giustolisi.
An integrated modelling approach for the assessment of land use change effects on wastewater infrastructures.
Environmental Modelling & Software, 24 (2009 dec), pp. 1522-1528
[Ekman et al., 2006]
M. Ekman, B. Björlenius, M. Andersson.
Control of the aeration volume in an activated sludge process using supervisory control strategies.
Water research, 40 (2006), pp. 1668-1676
[Flores-Alsina et al., 2014]
X. Flores-Alsina, M. Arnell, Y. Amerlinck, L. Corominas, K.V. Gernaey, L. Guo, E. Lindblom, I. Nopens, J. Porro, A. Shaw, L. Snip, P.A. Vanrolleghem, U. Jeppsson.
Balancing effluent quality, economic cost and greenhouse gas emissions during the evaluation of (plant-wide) control/operational strategies in WWTPs.
Science of The Total Environment, (2014 jan), pp. 466-467
616-624
[Flores-Alsina et al., 2011]
X. Flores-Alsina, L. Corominas, L. Snip, P.A. Vanrolleghem.
Including greenhouse gas emissions during benchmarking of wastewater treatment plant control strategies.
Water Research, 45 (2011 oct), pp. 4700-4710
[Flores-Alsina et al., 2008]
X. Flores-Alsina, I. Rodríguez-Roda, G. Sin, K.V. Gernaey.
Multicriteria evaluation of wastewater treatment plant control strategies under uncertainty.
Water research, 42 (2008), pp. 4485-4497
[Francisco et al., 2015]
M. Francisco, S. Skogestad, P. Vega.
Model predictive control for the self-optimized operation inwastewater treatment plants: Analysis of dynamic issues.
Computers and Chemical Engineering, 82 (2015), pp. 259-272
[Fu and Butler, 2012]
G. Fu, D. Butler.
Frequency analysis of river water quality using integrated urban wastewater models.
Water Science & Technology, 65 (2012 may), pp. 2112
[Fu et al., 2010]
G. Fu, S.-T. Khu, D. Butler.
Optimal distribution and control of storage tank to mitigate the impact of new developments on receiving water quality.
Journal of Environmental Engineering, 136 (2010 mar), pp. 335-342
[Gernaey and Jørgensen, 2004]
K.V. Gernaey, S.B. Jørgensen.
Benchmarking combined biological phosphorus and nitrogen removal wastewater treatment processes.
Control Engineering Practice, 12 (2004 mar), pp. 357-373
[Güçlü and Dursun, 2010]
D. Güçlü, S. Dursun.
Artificial neural network modelling of a largescale wastewater treatment plant operation.
Bioprocess and Biosystems Engineering, 33 (2010), pp. 1051-1058
[Guerrero et al., 2012]
J. Guerrero, A. Guisasola, J. Comas, I. Rodríguez-Roda, J. Baeza.
Multi-criteria selection of optimum WWTP control setpoints based on microbiology-related failures, effluent quality and operating costs.
Chemical Engineering Journal, 188 (2012 apr), pp. 23-29
[Guo et al., 2012]
L. Guo, J. Porro, K.R. Sharma, Y. Amerlinck, L. Benedetti, I. Nopens, A. Shaw, S.W.H.V. Hulle, Z. Yuan, P.A. Vanrolleghem.
Towards a benchmarking tool for minimizing wastewater utility greenhouse gas footprints.
Water Science & Technology, 66 (2012 oct), pp. 2483
[Han et al., 2008]
Y. Han, M. Brdys, R. Piotrowski.
Nonlinear pi control for dissolved oxygen tracking at wastewater treatment plant.
Korea, (2008 6-11 July),
[Henze et al., 2002]
M. Henze, W. Gujer, T. Mino, M. van Loosedrecht.
Activated Sludge Models ASM1, ASM2, ASM2d and ASM3.
Scientific and Technical Reports, IWA Publishing, (2002),
No. 9
[Hiatt and Grady, 2008]
W.C. Hiatt, C.P.L. Grady.
An updated process model for carbon oxidation, nitrification, and denitrification.
Water Environment Research, 80 (2008 nov), pp. 2145-2156
[Holenda et al., 2008]
B. Holenda, E. Domokos, A. Redey, J. Fazakas.
Dissolved oxygen control of the activated sludge wastewater treatment process using model predictive control.
Computers and Chemicals Engineering, 32 (2008), pp. 1270-1278
[IFAK, 2007]
IFAK.
SIMBA Manual and Reference.
Insitut fuer Automation und Kom-munikation e. V, Magdeburg, (2007),
[Ingildsen, 2002]
P. Ingildsen.
Realising full-scale control in wastewater treatment systems using in situ nutrient sensors.
Ph. D. thesis, Department of Industrial Electrical Engineering and Automation, (2002),
[Ingildsen et al., 2002]
P. Ingildsen, G. Olsson, Z. Yuan.
A hedging point strategy–balancing effluent quality, economy and robustness in the control of wastewater treatment plants.
Water science and technology, 45 (2002), pp. 317-324
[Jager, 1995]
R. Jager.
Fuzzy logic in control.
Ph. D. thesis, Delft University of Technology, (1995),
[Jeppsson et al., 2013]
U. Jeppsson, J. Alex, D.J. Batstone, L. Benedetti, J. Comas, J.B. Copp, L. Corominas, X. Flores-Alsina, K.V. Gernaey, I. Nopens, M.-N. Pons, I. Rodríguez-Roda, C. Rosen, J.-P. Steyer, P.A. Vanrolleghem, E.I.P. Volcke, D. Vrecko.
Benchmark simulation models,quo vadis?.
Water Science & Technology, 68 (2013 jul), pp. 1
[Kabouris and Georgakakos, 1990]
J. Kabouris, A. Georgakakos.
Optimal control of the activated sludge process.
Water Research, 24 (1990), pp. 1197-1208
[Kabouris et al., 1992]
J.C. Kabouris, A.P. Georgakakos, A. Camara.
Optimal control of the activated sludge process: Effect of sludge storage.
Water research, 26 (1992), pp. 507-517
[Kampschreur et al., 2008]
M.J. Kampschreur, N.C.G. Tan, R. Kleerebezem, C. Picioreanu, M.S.M. Jetten, M.C.M. van Loosdrecht.
Effect of dynamic process conditions on nitrogen oxides emission from a nitrifying culture.
Environmental Science & Technology, 42 (2008 jan), pp. 429-435
[Krause et al., 2002a]
K. Krause, K. Böcker, J. Londong.
Simulation of a nitrification control concept considering influent ammonium load.
Water Science and Technology, 45 (2002), pp. 413-420
[Krause et al., 2002b]
K. Krause, K. Böcker, J. Londong.
Simulation of a nitrification control concept considering influent ammonium load.
Water Science and Technology, 45 (2002), pp. 413-420
[Lijklema et al., 1993]
L. Lijklema, J.M. Tyson, A. Lesouef.
Interactions between sewers, treatment plants and receiving waters in urban areas: a summary of the interurba ‘92 workshop conclusions.
Water Science and Technolog, 27 (1993), pp. 1-29
[Lindberg and Carlsson, 1996a]
C. Lindberg, B. Carlsson.
Nonlinear and set-point control of the dissolved oxygen concentration in an activated sludge process.
Water Science and Technology, 34 (1996), pp. 135-142
[Lindberg and Carlsson, 1996b]
C.-F. Lindberg, B. Carlsson.
Adaptive control of external carbon flow rate in an activated sludge process.
Water science and technology, 34 (1996), pp. 173-180
[Lingireddy and Brion, 2005]
S. Lingireddy, G.M. Brion.
Artificial neural networks in water supply engineering.
ASCE Publications, (2005),
[Lukasse et al., 1998]
I. Lukasse, K. Keesman, A. Klapwijk, G. Vanstraten.
Optimal control of n-removal in ASPs.
Water Science and Technology, 38 (1998), pp. 255-262
[Lukasse et al., 1999]
L. Lukasse, K. Keesman, A. Klapwijk, G. Vanstraten.
A comparison of NH/NO control strategies for alternating activated sludge processes.
Water Science and Technology, 39 (1999), pp. 93-102
[Lukasse et al., 1997]
L.J.S. Lukasse, K.J. Keesman, A. Klapwijk, G. van Straten.
Adaptive receding horizon optimal control of n-removing activated sludge processes.
En: In Proc. of the 11th Forum for Applied Biotechnology, Univ. Gent, (1997), pp. 1665-1672
[Lynggaard-Jensen et al., 2010]
A. Lynggaard-Jensen, F. anf, P.A. Husum, M. Nygaard, J. Kaltoft, L. Landgren, F. Møller, E.E. Brodersen.
Increased performance of secondary clarifiers using dynamic distribution of minimum return sludge rates.
Water Science Technology, 60 (2010), pp. 2439-2445
[Machado et al., 2009]
V.C. Machado, D. Gabriel, J. Lafuente, J.A. Baeza.
Cost and effluent quality controllers design based on the relative gain array for a nutrient removal WWTP.
Water Research, 43 (2009 dec), pp. 5129-5141
[Maeda et al., 1990]
K. Maeda, S. Inoue, J. Hirotsuji, M. Nonoyama, S. Aya.
A new expert system based on deep knowledge for water and wastewater treatment plant. En: In Proc. of the. 5th IAWPRC Workshop on Instrumentation.
Control and Automation of Water and Wastewater Treatment and Transport Systems, Pergamon, Yokohama and Kyoto, (1990), pp. 219-226
[Maere et al., 2011]
T. Maere, B. Verrecht, S. Moerenhout, S. Judd, I. Nopens.
BSMMBR: A benchmark simulation model to compare control and operational strategies for membrane bioreactors.
Water Research, 45 (2011 mar), pp. 2181-2190
[Marsili-Libelli, 1984]
S. Marsili-Libelli.
Optimal control of the activated sludge process.
Transactions of the Institute of Measurement and Control, 6 (1984), pp. 146-152
[Marsili-Libelli, 1989]
S. Marsili-Libelli.
Modelling, identification and control of the activated sludge process.
Springer Berlin Heidelberg, (1989), pp. 89-148 http://dx.doi.org/10.1007/BFb0007860
URL: http://dx.doi.org/10.1007/BFb0007860
[Meirlaen et al., 2002]
J. Meirlaen, J. Van Assel, P.A. Vanrolleghem.
Real time control of the integrated urban wastewater system using simultaneously simulating surrogate models.
Wat. Sci. Tech, 45 (2002), pp. 109-116
[Meneses et al., 2016]
M. Meneses, H. Concepción, R. Vilanova.
Joint environmental and economical analysis of wastewater treatment plants control strategies: A benchmark scenario analysis.
Sustainability, 8 (2016 apr), pp. 360
[Meneses et al., 2015]
M. Meneses, H. Concepción, D. Vrecko, R. Vilanova.
Life cycle assessment as an environmental evaluation tool for control strategies in wastewater treatment plants.
Journal of Cleaner Production, 107 (2015 nov), pp. 653-661
[Meyer and Pöpel, 2003]
U. Meyer, H. Pöpel.
Fuzzy-control for improved nitrogen removal and energy saving in wwt-plants with pre-denitrification.
Water Science and Technology, 47 (2003), pp. 69-76
[Nasr et al., 2014]
M. Nasr, M. Moustafa, H. Seif, G. El-Kobrosy.
Application of fuzzy logic control for benchmark simulation model 1.
Sustainable Environment Research, 24 (2014),
[Ni et al., 2012]
B.-J. Ni, Z. Yuan, K. Chandran, P.A. Vanrolleghem, S. Murthy.
Evaluating four mathematical models for nitrous oxide production by autotrophic ammonia-oxidizing bacteria.
Biotechnology and Bioengineering, 110 (2012 aug), pp. 153-163
[Olsson et al., 1989]
G. Olsson, B. Andersson, B.G. Hellstrom, H. Holmström, L.G. Reinius, P. Vopatek.
Measurements, data analysis and control methods in wastewater treatment plants–state of the art and future trends.
Water Science and Technology, 21 (1989), pp. 1333-1345
[Olsson et al., 1998]
G. Olsson, H. Aspegren, M. Nielsen.
Operation and control of wastewater treatment — a scandinavian perspective over 20 years.
Water Science and Technology, 37 (1998), pp. 1-13
[Olsson and Newell, 1999]
G. Olsson, B. Newell.
Wastewater treatment systems: modelling, diagnosis and control.
IWA publishing, (1999),
[Olsson et al., 2005]
G. Olsson, M. Nielsen, Z. Yuan, A. Lynggaard-Jensen, J.-P. Steyer.
Instrumentation, control and automation in wastewater systems.
IWA publishing, (2005),
[Olsson et al., 1985]
G. Olsson, L. Rundqwist, L. Eriksson, L. Hall.
Instrumentation and Control of Water and Wastewater Treatment and Transport Systems, Advances in Water Pollution Control. Int Association on Water Pollution Research and Control.
Ch. Self-tuning control of the dissolved oxygen concentration in activated sludge systems, (1985), pp. 473-480
[Ostace et al., 2013]
G.S. Ostace, J.A. Baeza, J. Guerrero, A. Guisasola, V.M. Cristea, P.Ş. Agachi, J. Lafuente.
Development and economic assessment of different WWTP control strategies for optimal simultaneous removal of carbon, nitrogen and phosphorus.
Computers & Chemical Engineering, 53 (2013 jun), pp. 164-177
[Pan et al., 2013]
Y. Pan, B.-J. Ni, Z. Yuan.
Modeling electron competition among nitrogen oxides reduction and n2o accumulation in denitrification.
Environmental Science & Technology, 47 (2013 oct), pp. 11083-11091
[Peng et al., 2005]
Y. Peng, Y. Ma, S. Wang, X. Wang.
Fuzzy control of nitrogen removal in predenitrification process using orp.
Water science and technology, 52 (2005), pp. 161-169
[Piotrowski et al., 2008]
R. Piotrowski, M. Brdys, K. Konarczak, K. Duzinkiewicz, W. Chotkowski.
Hierarchical dissolved oxygen control for activated sludge processes.
Control Engineering Practice, 16 (2008), pp. 114-131
[Rauch et al., 2002]
W. Rauch, J.L. Bertrand-Krajewski, P. Krebs, O. Mark, W. Schilling, M. Schütze, P.A. Vanrolleghem.
Deterministic modelling of integrated urban drainage systems.
Wat. Sci. Tech., 45 (2002), pp. 81-94
[Rauch, 1999]
W. Rauch, P. Harremoës.
Genetic algorithms in real time control applied to minimize transient pollution from urban wastewater systems.
Water Research, 33 (1999 apr), pp. 1265-1277
[Revollar et al., 2015]
S. Revollar, P. Vega, R. Vilanova.
Economic optimization of wastewa-ter treatment plants using Non Linear Model Predictive Control.
En: 19th International Conference on System Theory, Control and Computing, Cheile Gradistei, (2015 14-16 October),
[Rieger et al., 2003]
L. Rieger, J. Alex, S. Winkler, M. Boehler, M. Thomann, H. Siegrist.
Progress in sensor technology progress in process control?. part i: Sensor property investigation and classification.
Water Sci. Technolgy, 47 (2003), pp. 103-111
[Rodriguez-Roda et al., 2002]
I. Rodriguez-Roda, M. Sánchez-Marré, J. Comas, J. Baeza, J. Colprim, J. Lafuente, U. Cortés, M. Poch.
A hybrid supervisory system to support wwtp operation: implementation and validation.
Water science and technology, 45 (2002), pp. 289-297
[Rojas et al., 2011]
J. Rojas, J.A. Baeza, R. Vilanova.
Effect of the controller tuning on the performance of the bsm1 using a data driven approach.
En: Proceedings of the 8th International IWA Symposium on Systems Analysis and Integrated Assessment in Water Management, San Sebastián, (2011),
[Rojas et al., 2012]
J.D. Rojas, X. Flores-Alsina, U. Jeppsson, R. Vilanova.
Application of multivariate virtual reference feedback tuning for wastewater treatment plant control.
Control Engineering Practice, 20 (2012), pp. 499-510
[Rossman, 2009]
L. Rossman.
Storm water management model user's manual version 5.0. epa/600/r05/040,. Tech. rep.
National Risk Management Research Laboratory, United States Environmental Protection Agency, (2009),
[Samie et al., 2011]
G. Samie, J. Bernier, V. Rocher, P. Lessard.
Modeling nitrogen removal for a denitrification biofilter.
Bioprocess and Biosystems Engineering, 34 (2011 feb), pp. 747-755
[Samuelsson and Carlsson, 2001]
P. Samuelsson, B. Carlsson.
Feed-forward control of the external carbon flow rate in an activated sludge process.
Water science and technology: a journal of the International Association on Water Pollution Research, 43 (2001), pp. 115-122
[Samuelsson et al., 2007]
P. Samuelsson, B. Halvarsson, B. Carlsson.
Cost-efficient operation of a denitrifying activated sludge process.
Water research, 41 (2007), pp. 2325-2332
[Santín et al., 2015a]
I. Santín, C. Pedret, R. Vilanova.
Applying variable dissolved oxygen set point in a two level hierarchical control structure to a wastewater treatment process.
Journal of Process Control, 28 (2015 a), pp. 40-55
[Santín et al., 2015b]
I. Santín, C. Pedret, R. Vilanova.
Fuzzy control and Model Predictive Control Configurations for Effluent Violations Removal in Wastewater Treatment Plants.
Industrial and Engineering Chemistry Research, 54 (2015 b), pp. 2763-2775
[Santiń et al., 2016a]
I. Santiń, C. Pedret, R. Vilanova.
Control and Decision Strategies in Wastewater Treatment Plants for Operation Improvement.
Springer, (2016),
[Santiń et al., 2016b]
I. Santín, C. Pedret, R. Vilanova, M. Meneses.
Advanced decision control system for effluent violations removal in wastewater treatment plants.
Control Engineering Practice, 279 (2016), pp. 207-219
[Schmitt and Huber, 2006]
T. Schmitt, W. Huber.
The scope of integrated modelling: system boundaries, sub-systems, scales and disciplines.
Water Science & Technology, 54 (2006 oct), pp. 405
[Schutze et al., 2011]
M. Schutze, D. Butler, B.M. Beck.
Modelling, Simulation and Control of Urban Wastewater Systems.
Springer London, (2011),
[Schutze et al., 1999]
M. Schutze, D. Butler, M. Beck.
Optimisation of control strategies for the urban wastewater system?. an integrated approach.
Water Science and Technology, 39 (1999), pp. 209-216
[Serralta et al., 2002]
J. Serralta, J. Ribes, A. Seco, J. Ferrer.
A supervisory control system for optimising nitrogen removal and aeration energy consumption in wastewater treatment plants.
Water Science and Technology, 45 (2002), pp. 309-316
[Shanahan et al., 2001]
P. Shanahan, D. Borchardt, M. Henze, W. Rauch, P. Reichert, L. Somlyódy, P. Vanrolleghem.
River water quality model no. 1 (rwqm1): I. modelling approach.
Water Science and Technology, 43 (2001), pp. 1-9
URL: http://wst.iwaponline.com/content/43/5/1
[Shen et al., 2009]
W. Shen, X. Chen, M. Pons, J. Corriou.
Model predictive control for wastewater treatment process with feedforward compensation.
Chemical Engineering Journal, 155 (2009), pp. 161-174
[Singman, 1999]
J. Singman.
Efficient control of wastewater treatment plant? a benchmark study. Master's thesis.
Department of Earth Sciences, Uppsala University, (1999),
[Stare et al., 2007a]
A. Stare, D. Vrecko, N. Hvala, S. Strmcnick.
Comparison of control strategies for nitrogen removal in an activated sludge process in terms of operating costs: A simulation study.
Water Research, 41 (2007 a), pp. 2004-2014
[Stare et al., 2007b]
A. Stare, D. Vrečko, N. Hvala, S. Strmčnik.
Comparison of control strategies for nitrogen removal in an activated sludge process in terms of operating costs: A simulation study.
Water Research, 41 (may 2007 b), pp. 2004-2014
[Steffens and Lant, 1999]
M. Steffens, P. Lant.
Multivariable control of nutrient-removing activated sludge systems.
Water Research, 33 (aug 1999), pp. 2864-2878
[Stephanopoulos and Ng, 2000]
G. Stephanopoulos, C. Ng.
Perspectives on the synthesis of plantwide control structures.
Journal of Process Control, 10 (apr 2000), pp. 97-111
[Stepner and Petersack, 1974]
D. Stepner, J. Petersack.
Progress in Water Technology, Vol. 6, Instrumentation, Control and Automation for Wastewater Treatment Systems.
Ch. Date management and computerized control of a secondary waste-water-treatment plant, Pergamon Press, (1974), pp. 417-423
[Steyer et al., 2006]
J.P. Steyer, O. Bernard, D.J. Batstone, I. Angelidaki.
Lessons learnt from 15 years of ICA in anaerobic digesters.
Water Science and Technology, 53 (feb 2006), pp. 25-33
[Traoré et al., 2006]
A. Traoré, S. Grieu, F. Thiery, M. Polit, J. Colprim.
Control of sludge height in a secondary settler using fuzzy algorithms.
Computers & Chemical Engineering, 30 (jun 2006), pp. 1235-1242
[Vanrolleghem, 1994]
P. Vanrolleghem.
On-line modeling of activated sludge processes: development of an adaptive sensor.
Ph. D. thesis, University of Gent, (1994),
[Vanrolleghem et al., 2004]
P. Vanrolleghem, L. Benedetti, J. Meirlaen.
Modelling and real-time control of the integrated urban wastewater system.
Environmental Modelling & Software, 20 (apr 2005), pp. 427-442
[Vanrolleghem and Gillot, 2002a]
P.A. Vanrolleghem, S. Gillot.
Robustness and economic measures as control benchmark performance criteria.
Water Science and Technology, 45 (2002 a), pp. 117-126
[Vanrolleghem and Gillot, 2002b]
P.A. Vanrolleghem, S. Gillot.
Robustness and economic measures as control benchmark performance criteria.
Water Science and Technology, 45 (2002 b), pp. 117-126
[Vanrolleghem et al., 1996]
P.A. Vanrolleghem, U. Jeppsson, J. Carstensen, B. Carlssont, G. Olsson.
Integration of wastewater treatment plant design and operation: a systematic approach using cost functions.
Water Science and Technology, 34 (1996), pp. 159-171
[Vilanova and Alfaro, 2011]
R. Vilanova, V.M. Alfaro.
Control PID robusto: Una visión panorámica.
Revista Iberoamericana de Automática e Informática Industrial RIAI, 8 (2011), pp. 141-148
[Vilanova et al., 2009]
R. Vilanova, R. Katebi, V. Alfaro.
Multi-loop pi-based control strategies for the activated sludge process. En: In Proc. of the IEEE Conference on Emerging Technologies Factory Automation (ETFA).
Mallorca, (2009 22-26 September),
[Vilanova et al., 2011]
R. Vilanova, R. Katebi, N. Wahab.
N-removal on wastewater treatment plants: A process control approach.
Journal of Water Resource and Protection, 3 (2011), pp. 1-11
[Vilanova et al., 2017]
R. Vilanova, I. SantÃín, C. Pedret.
Control y operación de estaciones depuradoras de aguas residuales: Modelado y simulación.
Revista Iberoamericana de Automática e Informática Industrial RIAI, 14 (2017), pp. 217-233
[Vitasovic and Andrews, 1989]
Z. Vitasovic, J. Andrews.
An integrated dynamic model and control system for activated sludge wwtp's part ii contol systems.
Water Poll. Res. J. Canada, 24 (1989), pp. 49722
[Vrečko et al., 2006]
D. Vrečko, N. Hvala, A. Stare, O. Burica, M. Strazar, M. Levstek, P. Cerar, S. Podbevsek.
Improvement of ammonia removal in activated sludge process with feedforward-feedback aeration controllers.
Water Science Technology, 53 (2006), pp. 125-132
[Vrečko et al., 2011]
D. Vrečko, N. Hvala, M. Strazar.
The application of model predictive control of ammonia nitrogen in an activated sludge process.
Water Science and Technology, 64 (2011), pp. 1115-1121
[Wahab and Katebi, 2009]
N.A. Wahab, J.R.B. Katebi.
Multivariable PID control design for activated sludge process with nitrication and denitrication.
Biochemical Engineering Journal, 45 (2009), pp. 239-248
[Yamanaka et al., 2006]
O. Yamanaka, T. Obara, K. Yamamoto.
Total cost minimization control scheme for biological wastewater treatment process and its evaluation based on the cost benchmark process.
Water science and technology: a journal of the International Association on Water Pollution Research, 53 (2006), pp. 203-214
[Yong et al., 2006a]
M. Yong, P. Yong-zhen, W. Xiao-lian, W. Shu-ying.
Intelligent control aeration and external carbon addition for improving nitrogen removal.
Environmental Modelling & Software, 21 (jun 2006 a), pp. 821-828
[Yong et al., 2006b]
M. Yong, P. Yongzhen, U. Jeppsson.
Dynamic evaluation of integrated control strategies for enhanced nitrogen removal in activated sludge processes.
Control Engineering Practice, 14 (2006 b), pp. 1269-1278
[Yuan and Blackall, 2002]
Z. Yuan, L.L. Blackall.
Sludge population optimisation: a new dimension for the control of biological wastewater treatment systems.
Water Research, 36 (2002 jan), pp. 482-490
[Yuan et al., 2002a]
Z. Yuan, H. Bogaert, C. Rosen, W. Verstraete.
Sludge blanket height control in secondary clarifiers.
Water Intelligence Online, (2002),
[Yuan and Keller, 2003]
Z. Yuan, J. Keller.
Integrated control of nitrate recirculation and external carbon addition in a predenitrification system.
Water science and technology : a journal of the International Association on Water Pollution Research, 48 (2003), pp. 345-354
[Yuan et al., 2002b]
Z. Yuan, A. Oehmen, P. Ingildsen.
Control of nitrate recirculation flow in predenitrication systems.
Water Science and Technology, 45 (2002), pp. 29-36
[Zhao and Chai, 2005]
L. Zhao, T. Chai.
In Advances in neural networks. Second international symposium on neural networks.
Ch. Wastewater BOD forecasting model for optimal operation using robust time delay neural network, (2005),
[Zhu et al., 2009]
G. Zhu, Y. Peng, B. Ma, Y. Wang, C. Yin.
Optimization of anoxic/oxic step feeding activated sludge process with fuzzy control model for improving nitrogen removal.
Chemical Engineering Journal, 151 (2009), pp. 195-201
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