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Wastewater treatment is a problem known to humankind for centuries. The quality of treated sewage determines the condition of reservoirs around the world. Control of such a complex and nonlinear system as a wastewater treatment plant requires thorough knowledge of the process. The paper presents a hierarchical control system of a Sequencing Batch Reactor (SBR) in Wastewater Treatment Plant (WWTP) taking into account a model based on actual measurements taken from a WWTP in Swarzewo, Poland. The authors designed and implemented a nonlinear model predictive controller (MPC) that allows for the optimal implementation of the desired DO level while minimising the operation of actuators (aeration system). The design description of the predictive controller was associated with the need to specify the performance function and define the optimisation problem. In a two-layer structure, a supervisory controller was implemented based on an actual time-based controller in Swarzewo WWTP. The overview showed the improved performance of the treatment plant and the versatility of the created solution. Results of simulation tests for the wastewater treatment plant case study are presented. • Dissolved oxygen control is very important for WWTP energy efficiency. • The process of designing a hierarchical control system of a SBR has been presented. • Nonlinear MPC has been applied for optimal implementation of the set DO trajectory. • Results of simulation tests for WWTP case study have been presented. [ABSTRACT FROM AUTHOR]

The paper presents the complete design processes of novel aeration control systems in the SBR (sequencing batch reactor) wastewater treatment plant (WWTP). Due to large energy expense and a high influence on biological processes, the aeration system plays a key role in WWTP operation. The paper considers the aeration system for a biological WWTP located in the northeast of Poland. This system consists of blowers, the main collector pipeline, three aeration lines with different diameters and lengths, and diffusers. Classical control systems applied for this type of installation are based on PID (proportional–integral–derivative) controllers, the settings of which are often found experimentally. The article presents the optimization of these settings and the design of an alternative control algorithm—the fuzzy controller. [ABSTRACT FROM AUTHOR]