EVALUATION OF CONTROL TECHNIQUES APPLIED ON A WASTEWATER TREATMENT PROCESS WITH ACTIVATED SLUDGE

Wastewater treatment processes with activated sludge are described in the specialized literature by complex models with nonlinear parameterization, such as for example Activated Sludge Model ASM1, ASM2 or ASM3. Under these conditions, the design of control structures using the state space representation is very difficult. Suitable techniques to approach the control of these processes are using control structures based on an input-output model or using control structures obtained without even knowing the process model. In this paper two techniques of this type are analyzed: a data driven technique, Virtual Reference Feedback Tuning (VRFT), and a robust control technique, Quantitative Feedback Theory (QFT). The control structures designed by the two methods are implemented using a wastewater treatment plant implemented in the simulation software SIMBA for which a complex influent was considered. The influent includes information on water temperature and gives data for a period of one year. The analysis of the two methods considers the quality of the obtained control results but, at the same time, the difficulty of implementing the two methods.

[1]  Hong Wang,et al.  Improvement of nitrogen removal and reduction of operating costs in an activated sludge process with feedforward–cascade control strategy , 2008 .

[2]  Constantine Garcia-Sanz,et al.  Wind Energy Systems: Control Engineering Design , 2012 .

[3]  L Åmand,et al.  Aeration control - a review. , 2013, Water science and technology : a journal of the International Association on Water Pollution Research.

[4]  M. C. Campia,et al.  Virtual reference feedback tuning: a direct method for the design of feedback controllers , 2002 .

[5]  N Hvala,et al.  Comparison of control strategies for nitrogen removal in an activated sludge process in terms of operating costs: a simulation study. , 2007, Water research.

[6]  Barry Lennox,et al.  Model predictive control of an activated sludge process: A case study , 2011 .

[7]  Sylvie Gillot,et al.  The COST Simulation Benchmark: Description and Simulator Manual , 2001 .

[8]  Ulf Jeppsson,et al.  Application of multivariate virtual reference feedback tuning for wastewater treatment plant control , 2012 .

[9]  Isaac Horowitz,et al.  Optimum loop transfer function in single-loop minimum-phase feedback systems† , 1973 .

[10]  Ulf Jeppsson,et al.  Dynamic influent pollutant disturbance scenario generation using a phenomenological modelling approach , 2011, Environ. Model. Softw..

[11]  George Ifrim,et al.  QFT Control of Dissolved Oxygen Concentration in a Wastewater Treatment Pilot Plant , 2010 .

[12]  Fatiha Nejjari,et al.  Non-linear multivariable adaptive control of an activated sludge wastewater treatment process , 1999 .

[13]  Marian Barbu,et al.  QFT MULTIVARIABLE CONTROL OF A BIOLOGICAL WASTEWATER TREATMENT PROCESS USING ASM1 MODEL , 2007 .

[14]  Sergio M. Savaresi,et al.  Virtual reference feedback tuning: a direct method for the design of feedback controllers , 2002, Autom..

[15]  Paul Serban Agachi,et al.  EVALUATION OF DIFFERENT CONTROL STRATEGIES OF THE WASTE WATER TREATMENT PLANT BASED ON A MODIFIED ACTIVATED SLUDGE MODEL NO. 3 , 2012 .

[16]  Shervin Jamshidi,et al.  OPTIMIZATION OF ANAEROBIC BAFFLED REACTOR (ABR) USING ARTIFICIAL NEURAL NETWORK IN MUNICIPAL WASTEWATER TREATMENT , 2014 .

[17]  Marian Barbu,et al.  Predictive Control of a Wastewater Treatment Process , 2007, Int. J. Comput. Commun. Control.

[18]  Marian Barbu,et al.  Robust control of an activated sludge wastewater treatment process , 2013, 2013 17th International Conference on System Theory, Control and Computing (ICSTCC).