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Evaluation of Control Strategies in Activated Sludge Process for Biological Wastewater Treatment

B. Vivekanandan and A. Seshagiri Rao


In this paper, benchmark simulation model no.1 (BSM1) of an activated sludge process is used to evaluate various control strategies. Control configurations such as feedback control and feed-forward plus feedback (FF-FB) control are applied and compared with respect to effluent discharge requirements under specified constraints and operating costs. Feed-forward control is incorporated in the PI control configuration for preventing the influent loading disturbance affecting the process. No case studies of BSM1 model have been reported in the literature for the Indian wastewater. In this work, the dynamic simulation of an activated sludge process is performed using the data collected from the sewage treatment plant, located in India. The influent load data are collected during the dry weather period. The influent fractionation is carried out using the activated sludge model no.1 (ASM1). The results of the dynamic simulation indicate that FF-FB control of the activated sludge process is more effective than feedback control in meeting the constraints, especially effluent ammonia concentration which is considered as very important. From the comparison of performance evaluation criteria, it is observed that FF-FB control has achieved almost the same operating costs as with feedback control.


1. Wahab NA, Katebi R, Balderud J. Multivariable PID control design for activated sludge process with nitrification and denitrification. Biochem Eng J 2009;45:239–48.10.1016/j.bej.2009.04.016Search in Google Scholar

2. Stare A, Vrecko D, Hvala N, Strmcnik S. Comparison of control strategies for nitrogen removal in an activated sludge process in terms of operating costs: a simulation study. Water Res 2007;41:2004–14.10.1016/j.watres.2007.01.029Search in Google Scholar

3. Bing-Jie N, Wen-Ming X, Shao-Gen L, Han-Qing Y, Yi-Ping G, Jun Z, et al. Development of a mechanistic model for biological nutrient removal activated sludge systems and application to a full-scale WWTP. Environ Energy Eng 2010;56:1626–38.Search in Google Scholar

4. Henze M, Gujer W, Mino T, van Loosdrecht MCM. Activated Sludge Models ASM1, ASM2, ASM2d, and ASM3. London: IWA Publishing, 2000.10.2166/wst.1999.0036Search in Google Scholar

5. Shen W, Chen X, Corriou JP. Application of model predictive control to the BSM1 benchmark of wastewater treatment process. Comp Chem Eng 2008;32:2849–56.10.1016/j.compchemeng.2008.01.009Search in Google Scholar

6. Gernaey KV, Rosen C, Jeppsson U. WWTP dynamic disturbance modelling- an essential module for long term benchmarking development. Water Sci Technol 2006;53:225–34.10.2166/wst.2006.127Search in Google Scholar

7. Ingildsen P. 2002. Realising full-scale control in wastewater treatment systems using in situ nutrient sensors, Dissertation, Lund University.Search in Google Scholar

8. Vrecko D, Hvala N, Carlsson B. Feedforward-feedback control of an activated sludge process: a simulation study. Water Sci Technol 2003;47:19–26.10.2166/wst.2003.0623Search in Google Scholar

9. Alex J, BinhTo T, Hartwig P. Improved design and optimization of aeration control for WWTPs by dynamic simulation. Water Sci Technol 2002;45:365–72.10.2166/wst.2002.0626Search in Google Scholar

10. Yong M, Yongzhen P, Jeppsson U. Dynamic evaluation of integrated control strategies for enhanced nitrogen removal in activated sludge processes. Control Eng Pract 2006;14:1269–78.10.1016/j.conengprac.2005.06.018Search in Google Scholar

11. Samuelsson P, Halvarsson B, Carlsson B. Cost-efficient operation of a denitrifying activated sludge process. Water Res 2007;41:2325–32.10.1016/j.watres.2006.10.031Search in Google Scholar

12. Insel HG, Gorgun E, Artan N, Orhon D. Model based optimization of nitrogen removal in a full scale activated sludge plant. Environ Eng Sci 2009;26(3):471–80.10.1089/ees.2007.0272Search in Google Scholar

13. Araujo AC, Gallani S, Mulas M, Olsson G. Systematic approach to the design of operation and control policies in activated sludge systems. Ind Eng Chem Res 2011;50:8542–57.10.1021/ie101703sSearch in Google Scholar

14. Shen T, Shi H, Jing H, Xiong H. Feedforward control for nitrogen removal in a pilot-scale anaerobic-anoxic-oxic plant for municipal waste water treatment. Front Environ Sci Eng China 2011;5:130–9.10.1007/s11783-010-0266-2Search in Google Scholar

15. Vrecko D, Hvala N, Strazar M. The application of model predictive control of ammonia nitrogen in an activated sludge process. Water Sci Technol 2011;64:1115–21.10.2166/wst.2011.477Search in Google Scholar

16. Amand L, Carlsson B. Optimal aeration control in a nitrifying activated sludge process. Water Res 2012;46:2101–10.10.1016/j.watres.2012.01.023Search in Google Scholar

17. Rieger L, Jones RM, Dold PL, Bott CB. Ammonia-based feedforward and feedback aeration control in activated sludge processes. Water Environment Research 2014;86(1):63–73.10.2175/106143013X13596524516987Search in Google Scholar

18. Gernaey KV, Jeppsson U, Vanrolleghem PA, Copp JB. Benchmarking of control strategies for wastewater treatment plants. Scientific and Technical Report Series No. 23. London: IWA Publishing, 2014.10.2166/9781780401171Search in Google Scholar

19. Copp JB. The COST simulation benchmark-description and simulator manual. Luxembourg: Office for Official Publications of the European Communities, 2002.Search in Google Scholar

20. Takacs I, Patry GG, Nolasco D. A dynamic model of the clarification thickening process. Water Res 1991;25:1263–71.10.1016/0043-1354(91)90066-YSearch in Google Scholar

21. Alex J, Benedetti L, Copp J, Gernaey KV, Jeppsson U, Nopens I, et al. Benchmark simulation model no. 1 (BSM1). Technical report, Dept. of Industrial Electrical Engineering and Automation. Sweden: Lund University, 2008.Search in Google Scholar

22. Marlin TE. Process control: designing processes and control systems for dynamic performance. New Delhi: Tata McGraw-Hill, 2000:278.Search in Google Scholar

Received: 2016-2-25
Revised: 2016-5-11
Accepted: 2016-5-18
Published Online: 2016-6-4
Published in Print: 2016-12-1

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