Sunday , April 2 2023

Supervisory Control System for Adaptive Phase and
Work Cycle Management of Sequencing Wastewater
Treatment Plant

Gdansk University of Technology, Faculty of Electrical and Control Engineering,
Narutowicza 11/12, 80-233 Gdansk, Poland,,,

Abstract: The paper presents the design of the integrated control system applied to Sequencing Batch Reactor (SBR) in a biological Wastewater Treatment Plant (WWTP) in Swarzewo, which operates under activated sludge technology. Based on the real data records, ASM2d biological processes model and aeration system model, hierarchical control system for dissolved oxygen tracking and cycle management is designed. Internal Model Controller (IMC) was applied to control the air flow at the lower control level. Higher level dissolved oxygen controller is based on Direct Model Reference Adaptive Control (DMRAC) method. The supervisory system performs management of reactor work cycle, determines the phase length, controls sludge age, calculates setpoint of dissolved oxygen and adapts parameters of the lower control layer. Proposed control system allowed to: increase the efficiency, improve the quality of outflow and reduce the cost of aeration and chemical treatment plant, in relation to existing solutions in case study plant.

Keywords: activated sludge, aeration, control, wastewater treatment, dynamic simulation, sequencing batch reactor.

>>Full text
P. HIRSCH, R. PIOTROWSKI, K. DUZINKIEWICZ, M. GROCHOWSKI, Supervisory Control System for Adaptive Phase and Work Cycle Management of Sequencing Wastewater Treatment Plant, Studies in Informatics and Control, ISSN 1220-1766, vol. 25(2), pp. 153-162, 2016.

  1. Introduction

1.1 General information

In industrial practice, two different types of activated sludge Wastewater Treatment Plant (WWTP) are used: Sequencing Batch Reactor (SBR) and WWTP with a continuous flow throughout the plant. In SBR, all biochemical processes occurs in one tank, in the predefined sequence. In the second type of plant, several tanks are connected by recirculation flows (internal and external). In this paper the SBR type of the WWTP is considered.

The SBR technology is widely used under small wastewater inflows conditions and may be designed using a single or multiple tanks in parallel. A typical work cycle involves five operational phases: filling, biochemical reactions (aerobic, anoxic, anaerobic), sedimentation, decantation and idle state.

A variety of different control strategies may be set up by selecting of number and sequence of SBR operational phases, in order to adjust SBR to specific working conditions of each WWTP. Because of this SBR gains operational flexibility, that allows this kind of WWTP to benefit from control system modernization. It has been shown that SBR pollutant removal efficiency can be greatly improved by application of step-feed control strategy [16]. A variant of this strategy is implemented in Swarzewo WWTP, Northern Poland, which is the case study considered in this paper. During the biochemical reaction phases, pollutions in the form of organic matter and nutrients (mainly phosphorus and nitrogen compounds) are degraded during the mineralization, nitrification, denitrification and enhanced biological phosphorus removal. Efficiency of those processes relay strongly on oxygen concentration, therefore high quality of DO control is crucial for fulfilment of discharge limits. The DO control is also important for WWTP energy efficiency, as the aeration system is responsible for 50-75% of plant power usage [1].

The supervisory control in continuous flow and SBR WWTPs is of a different nature. The main objective of the continuous flow WWTP supervisory controller is to determine the oxygen setpoint and recirculation flows, that will be sufficient to efficiently treat the wastewater. In the case of the SBR, objective of the supervisory controller is to manage the work cycle, namely the sequence and length of operational phases. Therefore SBR supervisory controller may be called work cycle controller.

1.2 Survey of related works

Broad range of control technologies have been researched and applied to DO control, e.g. adaptive controller [4,9,13], predictive controller [5,7,11,12,18], multivariable PID controller [19], fuzzy controller [3,14], fuzzy predictive controller [15,20]. Extensive review of DO control can be found in [1].

In [4] Direct Model Reference Adaptive Control (DMRAC) technology for DO tracking in Swarzewo case study was presented. Furthermore, analysis of the parameters of the adaptive controller for control quality was examined [13]. The authors used calibrated SBR Activated Sludge Model No. 2d (ASM2d) [8] coupled with validated aeration system model [14]. Simulations proved that the proposed solution provides satisfactory control quality in the case of most basic work cycles based on single filling pattern [4]. However, application of more complex cycle control strategies showed that discussed control system lacks adaptability. Classic DMRAC is ineffective when applied to SBR operating with step-feed strategy in occurrence of influent fluctuations. Hence, additional stepwise adaptation of DMRAC parameters (learning rates, anti-windup filter gains and starting points) was applied and examined in [9].

The most basic applications of SBR work cycle controllers are based on a fixed duration and composition of the work cycle and subsequent phases. Numerous studies were conducted on the optimal selection of these scenarios. In [2] the effect of total cycle time, phases duration and phase sequence on nutrient removal performance were examined. Systematic approach to examine and to determine the optimal operation strategy for nutrient removal was developed [16]. On-line method of phase duration optimization was presented in [10]. Discussed algorithm was based on measurements of oxidation reduction potential, dissolved oxygen and pH.

Upon these measurements, optimal end points of aerobic and anoxic phases were determined. In 2005 aerobic phase duration optimization was presented [17]. Authors examined possibility of using oxygen uptake rate measurements alongside fuzzy controller to determine nitrification termination.

1.3 Problem statement and main contribution

In order to take full advantage of the SBR capabilities, it is necessary to apply complex work cycle composition with the intermittent filling method. The overview of related works shows, that attempts were made to determine an optimal work cycle composition, but with an assumption of fixed cycle duration. Similarly, methods of optimal phase design were researched with an assumption of fixed work cycle composition. In this paper an attempt to combine the advantages of these two approaches is made. Supervisory controller is proposed for the on-line phase duration optimization with adaptive work cycle structure arranging. Moreover, DO controller that takes into account limitations of aeration system is applied in the control structure.

In most of previously described research works the dynamics and limitations of aeration system were omitted. However, the impact of aeration system on performance and control strategies of WWTP can be significant. This applies for the SBR especially, as the aeration system has to work in wide pressure range due to step-feed strategy used in this kind of plants. In this paper nonlinear dynamics and limitations of aeration system were coupled with biological processes in the SBR.

In summary, the aim of this paper is to design the supervisory control system for adaptive phase and work cycle management of SBR, in wide operating range. This paper further develops the research works presented in [4,9,13].


  1. ÅMAND, L., G. OLSSON, B. CARLSSON, Aeration Control – A Review, Water Sc. Tech., vol. 67(11), 2013, pp. 2374-2398.
  2. ARTAN, N., P. WILDERER, D ORHON, et al., Model Evaluation and Optimisation of Nutrient Removal Potential for Sequencing Batch Reactors, Water SA, vol. 28(4), 2002, pp. 423-432.
  3. 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, Comput. Chem. Eng., vol. 37, 2012, pp. 152-162.
  4. BŁASZKIEWICZ, K., R. PIOTROWSKI, K. DUZINKIEWICZ, A Model-Based Improved Control of Dissolved Oxygen Concentration in Sequencing Wastewater Batch Reactor, Stud. Inform. Control, vol. 23 (4), 2014, pp. 323-333.
  5. DUZINKIEWICZ, K., R. PIOTROWSKI, M. A. BRDYS, W. KUREK, W., Genetic Hybrid Predictive Controller for Optimized Dissolved-Oxygen Tracking at Lower Control Level, IEEE Trans. Control Syst. Technol., vol. 17(5), 2009, pp. 1183-1192.
  6. GARCIA, C. E., M. MORARI, Internal Model Control. A Unifying Review and Some New Results, Ind. Eng. Chem. Proc. Des. Dev., vol. 21(2), 1982, pp. 308-323.
  7. HAN, H.-G., J.-F. QIAO, Q.-L., CHEN, Model Predictive Control of Dissolved Oxygen Concentration based on a Self-organizing RBF Neural Network, Control Eng. Pract., vol. 20(4), 2012, pp. 465-476.
  8. HENZE, M., W. GUJER, T. MINO, M. van LOOSDRECHT, Activated Sludge Models ASM1, ASM2, ASM2d and ASM3. London: IWA Publ, 2007.
  9. HIRSCH, P., R. PIOTROWSKI, K. DUZINKIEWICZ, Two-step Model based Adaptive Controller for Dissolved Oxygen Control in Sequencing Wastewater Batch Reactor. MMAR 2015. IEEE, 2015, pp. 677-682.
  10. PAVŠELJ, N., N. HVALA, J. KOCIJAN, et al., Experimental Design of an Optimal Phase Duration Control Strategy used in Batch Biological Wastewater Treatment, ISA Trans., vol. 40(1), 2001, pp. 41-56.
  11. PIOTROWSKI, R., M. A. BRDYS, K. KONARCZAK, et al., Hierarchical Dissolved Oxygen Control for Activated Sludge Processes, Control Eng. Pract., vol. 16(1), 2008, pp. 114-131.
  12. PIOTROWSKI, R., Two-Level Multivariable Control System of Dissolved Oxygen Tracking and Aeration System for Activated Sludge Processes, Water Env. Res., vol. 87(1), 2015, pp. 3-13.
  13. PIOTROWSKI, R., K. BŁASZKIEWICZ, K. DUZINKIEWICZ, Analysis the Parameters of the Adaptive Controller for Quality Control of Dissolved Oxygen Concentration, Inf. Tech. Control, vol. 45(1), 2016, pp. 42-51.
  14. PIOTROWSKI, R., A. SKIBA, Nonlinear Fuzzy Control System for Dissolved Oxygen with Aeration System in Sequencing Batch Reactor, Inf. Tech. Control, vol. 44(2), 2015, pp. 182-195.
  15. SANTÍN, I., C. PEDRET, R. VILANOVA, Applying Variable Dissolved Oxygen Set Point in a Two Level Hierarchical Control Structure to a Wastewater Treatment Process, J. Proc. Ctrl, vol. 28, 2015, pp. 40-55.
  16. SIN, G., G. INSEL, D. S. LEE, P.A. VANROLLEGHEM, Optimal But Robust N and P Removal in SBRs: A Model-based Systematic Study of Operation Scenarios, Water Sci. Tech., vol. 50(10), 2004, pp. 97-105.
  17. TRAORÉ, A., L. COROMINAS, S. PUIG, et al., Dissolved Oxygen Control and Phases Duration Optimization in a Sequencing Batch Reactor Pilot Plant. Proc. 17th IMACS World Congress on Scientific Computation. France, Applied Mathematics and Simulation, 2005.
  18. VREČKO, D., N. HVALA, M. STRAŽAR, The Application of Model Predictive Control of Ammonia Nitrogen in an Activated Sludge Process, Water Sci. Tech., vol. 64(5), 2011, pp. 1115.
  19. WAHAB, N. A., R. KATEBI, J. BALDERUD, Multivariable PID Control Design for Activated Sludge Process with Nitrification and Denitrification, Bioch. Eng. J., vol. 45(3), 2009, pp. 239-248.
  20. YANG, T., W. QIU, Y. MA, et al., Fuzzy Model-based Predictive Control of Dissolved Oxygen in Activated Sludge Processes, Neurocomputing, vol. 136, 2014, pp. 88-95.