Instrumentation, Control and Automation in Wastewater Systems

nstrumentation, control and automation (ICA) in wastewater treatment systems is now an established and recognised area of technology in the profession. There are obvious incentives for ICA, not the least from an economic point of view. Plants are also becoming increasingly complex which necessitates automation and control. Instrumentation, Control and Automation in Wastewater Systems summarizes the state-of-the-art of ICA and its application in wastewater treatment systems and focuses on how leading-edge technology is used for better operation. The book is written for: * The practising process engineer and the operator, who wishes to get an updated picture of what is possible to implement in terms of ICA; * The process designer, who needs to consider the couplings between design and operation; * The researcher or the student, who wishes to get the latest technological overview of an increasingly complex field. There is a clear aim to present a practical ICA approach, based on a technical and economic platform. The economic benefit of different control and operation possibilities is quantified. The more qualitative benefits, such as better process understanding and more challenging work for the operator are also described. Several full-scale experiences of how ICA has improved economy, ease of operation and robustness of plant operation are presented. The book emphasizes both unit process control and plant wide operation.

[1]  G Olsson,et al.  Application of information technology to decision support in treatment plant operation. , 2003, Water science and technology : a journal of the International Association on Water Pollution Research.

[2]  Bernard P. A. Grandjean,et al.  NEURAL NETWORKS IN PROCESS CONTROL - A SURVEY , 1992 .

[3]  Wei-Ling Chiang,et al.  Effluent suspended solid control of activated sludge process by fuzzy control approach , 1996 .

[4]  Petre Stoica,et al.  Decentralized Control , 2018, The Control Systems Handbook.

[5]  Magnus Christensson,et al.  A comparison between ethanol and methanol as carbon sources for denitrification , 1994 .

[6]  A. Vanrolleghem,et al.  Sensors for anaerobic digestion: An overview , 1995 .

[7]  I. Jolliffe Principal Component Analysis , 2002 .

[8]  Julian Morris,et al.  Artificial neural networks in process estimation and control , 1992, Autom..

[9]  D Bixio,et al.  Feasibility of automatic chemicals dosage control--a full-scale evaluation. , 2002, Water science and technology : a journal of the International Association on Water Pollution Research.

[10]  G. K. Anderson,et al.  Determination of bicarbonate and total volatile acid concentration in anaerobic digesters using a simple titration , 1992 .

[11]  R. Haker,et al.  EXPERIENCES WITH ONLINE MEASURING INSTRUMENTS FOR SBR-OPERATION IN KALMAR , 1999 .

[12]  Barry M. Wise,et al.  The process chemometrics approach to process monitoring and fault detection , 1995 .

[13]  N. V. Bhat,et al.  Use of neural nets for dynamic modeling and control of chemical process systems , 1990 .

[14]  Pernille Ingildsen,et al.  Realising full-scale control in wastewater treatment systems using in situ nutrient sensors , 2002 .

[15]  P A Vanrolleghem,et al.  Status and future trends of ICA in wastewater treatment--a European perspective. , 2002, Water science and technology : a journal of the International Association on Water Pollution Research.

[16]  Peter J. Gawthrop,et al.  Neural networks for control systems - A survey , 1992, Autom..

[17]  Gustaf Olsson,et al.  Disturbance detection in wastewater treatment plants , 1998 .

[18]  M. K. Nielsen,et al.  Advanced computer control based on real and software sensors , 1996 .

[19]  G Olsson,et al.  A benchmark study of controlled emptying of equalization basins. , 2005, Water science and technology : a journal of the International Association on Water Pollution Research.

[20]  D. Archer,et al.  On‐line titration method for monitoring buffer capacity and total volatile fatty acid levels in anaerobic digesters , 1989, Biotechnology and bioengineering.

[21]  P A Vanrolleghem,et al.  On-line monitoring equipment for wastewater treatment processes: state of the art. , 2003, Water science and technology : a journal of the International Association on Water Pollution Research.

[22]  Alan Sillitoe,et al.  Raw material , 1972 .

[23]  B. Anderson,et al.  Optimal control: linear quadratic methods , 1990 .

[24]  Andrew G. Barto,et al.  Connectionist learning for control: an overview , 1990 .

[25]  Sara Hallin,et al.  METABOLIC PROPERTIES OF DENITRIFYING BACTERIA ADAPTING TO METHANOL AND ETHANOL IN ACTIVATED SLUDGE , 1998 .

[26]  Howard Jay Chizeck,et al.  Closed Loop Control , 1985 .

[27]  D. L. Hawkes,et al.  A new instrument for on-line measurement of bicarbonate alkalinity , 1993 .

[28]  D. Dochain,et al.  On-Line Estimation and Adaptive Control of Bioreactors , 2013 .

[29]  A. C. Di Pinto,et al.  ANAEROBIC PROCESS CONTROL BY AUTOMATED BICARBONATE MONITORING , 1990 .

[30]  Michael Johnson,et al.  Control engineering : an introductory course , 2002 .

[31]  G. Olsson,et al.  Benchmarking plant operation and instrumentation, control and automation in the wastewater industry , 2002 .

[32]  Denis Dochain,et al.  Adaptive identification and control algorithms for nonlinear bacterial growth systems , 1984, Autom..

[33]  André Pauss,et al.  Hydrogen monitoring in anaerobic sludge bed reactors at various hydraulic regimes and loading rates , 1993 .

[34]  Peter A. Vanrolleghem,et al.  Respirometry in Control of the Activated Sludge Process: Principles , 1998 .

[35]  Peter A. Vanrolleghem,et al.  Control of External Carbon Addition to Predenitrifying Systems , 1997 .

[36]  H.A.B. te Braake Neural Control of Biotechnological Processes , 1997 .

[37]  Peter A. Vanrolleghem,et al.  Evaluation of a rule-based control strategy for an equalization facility with technical/physical constraints , 1999, 1999 European Control Conference (ECC).

[38]  Frédéric Ehlinger,et al.  Control Parameter Variations in an Anaerobic Fluidised Bed Reactor Subjected to Organic Shockloads , 1992 .

[39]  Nadine Hilgent Identification et controle de processus autoregressifs non lineaires incertains : application a des procedes biotechnologiques , 1997 .

[40]  P Gras,et al.  Evaluation of a four year experience with a fully instrumented anaerobic digestion process. , 2002, Water science and technology : a journal of the International Association on Water Pollution Research.

[41]  James W. Garson,et al.  ‘Here’ and ‘Now’ , 1969 .

[42]  Gustaf Olsson Advancing ICA Technology by Eliminating the Constraints , 1993 .

[43]  Ken-ichi Funahashi,et al.  On the approximate realization of continuous mappings by neural networks , 1989, Neural Networks.

[44]  Alessandro Astolfi,et al.  Set-point regulation of an anaerobic digestion process with bounded output feedback , 2003, IEEE Trans. Control. Syst. Technol..

[45]  P A Vanrolleghem,et al.  Towards a benchmark simulation model for plant-wide control strategy performance evaluation of WWTPs. , 2006, Water science and technology : a journal of the International Association on Water Pollution Research.

[46]  Phillip D. Schnelle,et al.  Model predictive control of an industrial packed bed reactor using neural networks , 1995 .

[47]  Jérôme Harmand,et al.  Robust regulation of a class of partially observed nonlinear continuous bioreactors , 2002 .

[48]  Alfred E. Brenner,et al.  Moore's Law , 1997, Science.

[49]  S. Svoronos,et al.  Optimization of a Periodic Biological Process for Nitrogen Removal from Wastewater , 1996 .

[50]  Gustaf Olsson,et al.  Get more out of your wastewater treatment plant - complexity made simple , 2001 .

[51]  O Bernard,et al.  Advanced monitoring and control of anaerobic wastewater treatment plants: software sensors and controllers for an anaerobic digester. , 2001, Water science and technology : a journal of the International Association on Water Pollution Research.

[52]  Niels Kjølstad Poulsen,et al.  Grey box modeling of first flush and incoming wastewater at a wastewater treatment plant , 2000 .

[53]  Benjamin C. Kuo,et al.  Automatic control systems (7th ed.) , 1991 .

[54]  Stefano Marsili-Libelli,et al.  Adaptive fuzzy pattern recognition in the anaerobic digestion process , 1996, Pattern Recognit. Lett..

[55]  Theodora Kourti,et al.  Statistical Process Control of Multivariate Processes , 1994 .

[56]  Paolo Pavan,et al.  Fuzzy Control of an Anaerobic Digester for the Treatment of the Organic Fraction of Municipal Solid Waste (MSW) , 1993 .

[57]  Mogens Henze,et al.  Activated sludge models ASM1, ASM2, ASM2d and ASM3 , 2015 .

[58]  J Harmand,et al.  Software sensors for highly uncertain WWTPs: a new approach based on interval observers. , 2002, Water research.

[59]  Mogens Henze,et al.  Controlled Carbon Source Addition to an Alternating Nitrification-Denitrification Wastewater Treatment Process Including Biological P Removal , 1995 .

[60]  M. B. Beck,et al.  Fuzzy control of the activated sludge wastewater treatment process , 1980, Autom..

[61]  Kumpati S. Narendra,et al.  Identification and control of dynamical systems using neural networks , 1990, IEEE Trans. Neural Networks.

[62]  Kurt Hornik,et al.  Multilayer feedforward networks are universal approximators , 1989, Neural Networks.

[63]  John Odenckantz,et al.  Nonparametric Statistics for Stochastic Processes: Estimation and Prediction , 2000, Technometrics.

[64]  Damien J. Batstone High Rate Anaerobic Treatment of Complex Wastewater , 2000 .

[65]  W. Gujer,et al.  Activated sludge model No. 3 , 1995 .

[66]  H.J.L. van Can Efficient Mathematical Modeling for Bioprocesses - based on macroscopic balances and neural networks , 1997 .

[67]  D. T. Hill,et al.  A dynamic model for simulation of animal waste digestion , 1977 .

[68]  Oliver J. Hao,et al.  Alternating aerobic-anoxic process for nitrogen removal : process evaluation , 1996 .

[69]  A. J. Morris,et al.  Artificial neural networks in process engineering , 1991 .

[70]  D. Dochain,et al.  Adaptive control of anaerobic digestion processes—a pilot‐scale application , 1988, Biotechnology and bioengineering.

[71]  Yonghong Tan,et al.  Nonlinear one-step-ahead control using neural networks: Control strategy and stability design , 1996, Autom..

[72]  Gustaf Olsson,et al.  Integration of WWT Plant Design and Operation - a Systematic Approach Using Cost Functions , 1996 .

[73]  C. Rosen,et al.  Adaptive multiscale principal components analysis for online monitoring of wastewater treatment. , 2002, Water science and technology : a journal of the International Association on Water Pollution Research.

[74]  Klaus L. Andersen,et al.  Nutrient Removal: On-Line Measurements and Control Strategies , 1993 .

[75]  K. Buchauer,et al.  A comparison of two simple titration procedures to determine volatile fatty acids in influents to waste-water and sludge treatment processes , 1998 .

[76]  Willy Verstraete,et al.  Sludge Blanket Height Control in Secondary Clarifiers , 2001 .

[77]  A. D. Wheatley,et al.  An application of an adaptive control algorithm for the anaerobic treatment of industrial effluent , 1995 .

[78]  Masaru Ishida,et al.  Neural model‐predictive control of distributed parameter crystal growth process , 1995 .

[79]  M. Florentz,et al.  Oxidation-Reduction Potential (ORP) Regulation: A Way to Optimize Pollution Removal and Energy Savings in the Low Load Activated Sludge Process , 1987 .

[80]  D Cecil,et al.  Controlling nitrogen removal using redox and ammonium sensors. , 2003, Water science and technology : a journal of the International Association on Water Pollution Research.