Tuesday , October 23 2018

A Model-Based Improved Control of Dissolved Oxygen
Concentration in Sequencing Wastewater Batch Reactor

Karol BLASZKIEWICZ, Robert PIOTROWSKI, Kazimierz DUZINKIEWICZ
Gdansk University of Technology, Faculty of Electrical and Control Engineering,
Narutowicza 11/12, 80-233 Gdansk, Poland
karolblaszkieewicz@gmail.com, r.piotrowski@eia.pg.gda.pl, k.duzinkiewicz@eia.pg.gda.pl

Abstract: Biochemical processes at wastewater treatment plants are complex, nonlinear, time varying and multivariable. Moreover, relationships between processes are very strong. One of the most important issues is exerting proper control over dissolved oxygen levels during nitrification phase. This parameter has a very large impact on activity of microorganisms in activated sludge and on quality of pollution removal processes. Oxygen is supplied by aeration system which consists of many nonlinear elements (blowers, pipes, diffusers). In this paper, the sequencing batch reactor is applied and modelled. Also, the aeration system is modelled. Those models are validated based on real data sets. The adaptive control system with anti-windup filter is proposed and designed for tracking the reference trajectory of dissolved oxygen. Furthermore, the reference trajectory of dissolved oxygen is generated by the supervisory controller using NH4 measurements. Simulation results of control system are calculated for a case study plant located in Swarzewo, Northern Poland.

Keywords: aeration, adaptive control, cascade control, dissolved oxygen, nonlinear control, wastewater treatment.

>>Full text
CITE THIS PAPER AS:
Karol BLASZKIEWICZ, Robert PIOTROWSKI, Kazimierz DUZINKIEWICZ, A Model-Based Improved Control of Dissolved Oxygen Concentration in Sequencing Wastewater Batch Reactor, Studies in Informatics and Control, ISSN 1220-1766, vol. 23 (4), pp. 323-332, 2014.

  1. Introduction

Progressive development of technology and human population growth caused the amount of produced sewage to increase. Years of experience and scientific research, gave rise to the idea about biological wastewater treatment plants (WWTP). This biological-chemical-physical system is classified as complex, multivariable, time varying and nonlinear.

In industrial practice, two different types of WWTPs are used: sequencing batch reactor (SBR) and WWTP with a continuous flow throughout the plant. In this paper the SBR type of the WWTP was considered.

The SBR technology is widely used for small wastewater inflows and may be designed using a single or multiple tanks in parallel. A typical cycle involves five operational phases: filling, reactions (nitrification and denitrification), sedimentation, decantation and idle state. Biochemical reactions in SBR were described in detail in e.g. [1]. In [2] a complete review of experiences using SBR of different kinds is presented.

One of phases taking place in a SBR reactor is the nitrification phase. This stage has a very large impact on removal pollutions. The most important control parameter in this phase is the concentration of dissolved oxygen (DO). Improvement of oxygen level control in the reactor could increase quality of outflow and decrease incurred operating costs. The dynamics of DO is nonlinear. Hence, high quality control for all operating conditions can be hard to achieve by using simple control strategies, e.g. on/off control system, linear PID controller with fixed parameters.

Previous studies reported various structures and technologies of DO control system, e.g. predictive controller [3,4,5,6,7], multivariable PID controller [8,9], neural and fuzzy controllers [10,11]. Other DO control strategies using NH4, NO3 and PO4 measurements have been designed and tested, e.g. [12,13]. In most cases, the nonlinear dynamic of aeration system is omitted and treated as static element. However, this system is very complex and contains many nonlinear elements, e.g. blowers, pipes and diffusers. In this paper, as opposite of previous research works, nonlinear dynamic of aeration system is coupled with biological processes. Furthermore, beside DO measurement, NH4 measurement is included for control system design.

The paper was organized as follows. The Swarzewo WWTP case study was described in Section 2. The aeration system was presented in Section 3.

Design of control system was described in Section 4. Section 5 presents results of simulations and discussions. Conclusions were included in Section 6.

REFERENCES

  1. WILDERER, P. A., R. L. IRVINE, M. GORONSZY, Sequencing Batch Reactor Technology, Scientific and Technical Report No. 10, IWA Publishing, London, 2001.
  2. MACE, S., J. MATA-ALVAREZ, Utilization of SBR Technology for Wastewater Treatment: An Overview, Industrial & Engineering Chemistry Research, vol. 41(23), 2002, pp. 5539-5553.
  3. BRDYS, M. A., M. GROCHOWSKI, , T. GMINSKI, , K. KONARCZAK, , M. DREWA, Hierarchical Predictive Control of Integrated Wastewater Systems, Control Engineering Practice, vol. 16(6), 2008, pp. 751-767.
  4. HOLENDA, B., E. DOMOKOS, A. RÉDEY, J. FAZAKAS, Dissolved Oxygen Control of the Activated Sludge Wastewater Treatment Process using Model Predictive Control, Computers and Chemical Engineering, vol. 32(6), 2008, pp. 1270-1278.
  5. PIOTROWSKI, R., M. A. BRDYS, K. KONARCZAK, K. DUZINKIEWICZ, W. CHOTKOWSKI, Hierarchical Dissolved Oxygen Control for Activated Sludge Processes, Control Engineering Practice, vol. 16(1), 2008, pp. 114-131.
  6. PIOTROWSKI, R., Two-Level Multivariable Control System of Dissolved Oxygen Tracking and Aeration System for Activated Sludge Processes, Water Environment Research (in press), 2014.
  7. DUZINKIEWICZ, K., M. A. BRDYS, , W. KUREK, , R. PIOTROWSKI, Genetic Hybrid Predictive Controller for Optimised Dissolved Oxygen Tracking at Lower Control Level, IEEE Transactions on Control Systems Technology, vol. 17(5), 2009, vol. 1183-1192.
  8. WAHAB, N. A., R. KATEBI, J. BALDERUD, Multivariable PID Control Design for Activated Sludge Process with Nitrification and Denitrification, Biochemical Engineering Journal, vol. 45, 2009, pp. 239-248.
  9. IRATNI, A., R. KATEBI, M. MOSTEFAI, Non-linear State Dependent Differential Riccati States Filter for Wastewater Treatment Process, Studies in Informatics and Control, vol. 20(3), 2011, pp. 247-254.
  10. FAN, L., K. BOSHNAKOV, Fuzzy Logic based Dissolved Oxygen Control for SBR Wastewater Treatment Process, Proceedings of the 8th World Congress on Intelligent Control and Automation, Jinan, July 06-09, 2010, China.
  11. BELCHIOR, C. A. C., R. A. M. ARAÚJO, J. A. C. LANDECK, Dissolved Oxygen Control of the Activated Sludge Wastewater Treatment Process using Stable Adaptive Fuzzy Control, Computers and Chemical Engineering, vol. 37(10), 2012, pp. 152-162.
  12. VREČKO, D., HVALA, N., STRAŽAR, M., The Application of Model Predictive Control of Ammonia Nitrogen in an Activated Sludge Process, Water Science and Technology vol. 64(5), 2011, pp. 1115-1121.
  13. ÅMAND, L., B. CARLSSON, The Optimal Dissolved Oxygen Profile in a Nitrifying Activated Sludge Process – Comparisons with Ammonium Feedback Control, Water Science and Technology vol. 68(3), 2013, pp. 641-649.
  14. HENZE, M., W. GUJER, T. MINO, T. MATSUO, M. C. WENTZEL, G. v. R. MARAIS, M. C. M. van LOOSDRECHT, Activated Sludge Model No. 2d, ASM2d, Water Science and Technology vol. 39(1), 1999, pp. 165-182.
  15. KRAWCZYK, W., R. PIOTROWSKI, , M. A. BRDYS, W. CHOTKOWSKI, (). Modelling and Identification of Aeration Systems for Model Predictive Control of Dissolved Oxygen – Swarzewo Wastewater Treatment Plant Case Study, Proceedings of the 10th IFAC Symposium on Computer Applications in Biotechnology, Cancun, June 04-06, 2007, Mexico.
  16. MORARI, M., E. ZAFIRION, Robust Process Control, Prentice Hall, New York, 1989.
  17. SIMBA User’s Guide. 2014, Available: http://www.ifak-system.com/en/environme ntal-simulation/simba/.
  18. ÅSTRÖM, K.J., B. WITTENMARK, Adaptive Control, 2 edition. Prentice Hall, New York, 1994.

 

https://doi.org/10.24846/v23i4y201402