Fundamental nonlinearities of the reactor-settler interaction in the activated sludge process.

The activated sludge process can be modelled by ordinary and partial differential equations for the biological reactors and secondary settlers, respectively. Because of the complexity of such a system, simulation models are most often used to investigate them. However, simulation models cannot give general rules on how to control a complex nonlinear process. For a reduced-order model with only two components, soluble substrate and particulate biomass, general results on steady-state solutions have recently been obtained, such as existence, uniqueness and stability of solutions. The aim of the present paper is to utilize those results to formulate some implications of practical importance. In particular, strategies are described for the manual control of the effluent substrate concentration subject to the constraint that the settler is maintained in normal operation (with a sludge blanket in the thickening zone) in steady state. Such strategies contain how the two control parameters, the recycle and waste volumetric flow ratios, should be chosen for any (steady-state) values of the input variables.

[1]  Fangfang Zhang,et al.  The Control of Wastewater Treatment Process Based on Fuzzy Neural Network , 2006, 2006 6th World Congress on Intelligent Control and Automation.

[2]  Ingmar Nopens,et al.  A consistent modelling methodology for secondary settling tanks in wastewater treatment. , 2011, Water research.

[3]  Jean-Luc Gouzé,et al.  Dynamical study and robustness for a nonlinear wastewater treatment model , 2011 .

[4]  Stefan Diehl,et al.  A reduced-order ODE-PDE model for the activated sludge process in wastewater treatment: Classification and stability of steady states , 2013 .

[5]  A. Charef,et al.  An adaptive and predictive control strategy for an activated sludge process , 2000 .

[6]  Ingmar Nopens,et al.  Extending and calibrating a mechanistic hindered and compression settling model for activated sludge using in-depth batch experiments. , 2008, Water research.

[7]  H. Ito.  A dissipative approach to control of biological wastewater treatment plants based on entire nonlinear process models , 2004, Proceedings of the 2004 American Control Conference.

[8]  T. Chai,et al.  Hybrid Dynamic Model of Anoxic-Aeration Biological Wastewater Treatment Plant , 2006, 2006 6th World Congress on Intelligent Control and Automation.

[9]  F. N. Koumboulis,et al.  Two-stage robust control of substrate concentration for an activated sludge process. , 2008, ISA transactions.

[10]  Morton M. Denn,et al.  Dynamics and control of the activated sludge wastewater process , 1978 .

[11]  Raimund Bürger,et al.  A Model of Continuous Sedimentation of Flocculated Suspensions in Clarifier-Thickener Units , 2005, SIAM J. Appl. Math..

[12]  Stefan Diehl,et al.  A conservation Law with Point Source and Discontinuous Flux Function Modelling Continuous Sedimentation , 1996, SIAM J. Appl. Math..

[13]  Moshe Sheintuch,et al.  Steady state modeling of reactor-settler interaction , 1987 .

[14]  M. Darouach,et al.  A nonlinear observer design for an activated sludge wastewater treatment process , 2009 .

[15]  Moshe Sheintuch,et al.  Multiplicity patterns of activated-sludge with substrate-inhibition kinetics , 1993 .

[16]  J. Ph. Chancelier,et al.  Analysis of a Conservation PDE With Discontinuous Flux: A Model of Settler , 1994, SIAM J. Appl. Math..

[17]  Petia Georgieva,et al.  Adaptive λ-[lambda]-tracking control of activated sludge processes , 2005 .

[18]  R. Tzoneva.  Method for real time optimal control of the activated sludge process , 2007, 2007 Mediterranean Conference on Control & Automation.

[19]  A. Kienle,et al.  Conceptual Analysis of the Effect of Kinetics on the Stability and Multiplicity of a Coupled Bioreactor−Separator System Using a Cybernetic Modeling Approach , 2009 .