Supervisory control configurations design for nitrogen and phosphorus removal in wastewater treatment plants

Abstract

Model predictive control (MPC) and Fuzzy controllers are designed in a two‐level hierarchical supervisory control framework for control of activated sludge‐based wastewater treatment plants (WWTP) in order to efficiently remove nitrogen and phosphorus. Benchmark simulation model No.3 with a bio‐phosphorus (ASM3bioP) module is used as a working platform. The hierarchical control framework is used to alter the dissolved oxygen in the seventh reactor (DO7) to control ammonia. Lower‐level PI, MPC, and Fuzzy are used to control the nitrate levels in the fourth reactor (SNO4) by manipulating internal recycle (Qintr) and DO7 in the seventh tank by manipulating mass transfer coefficient (KLa7). MPC and Fuzzy are designed in the supervisory layer to alter the DO7 set‐point based on the ammonia composition in the seventh reactor (NH7). From the analysis, it is observed that the effluent quality is improved with a decrease in ammonia, TN, and TP. Though a little difference was observed in the cost for all the control strategies, a trade‐off is maintained between cost and percentage improvement of effluent quality. MPC‐MPC combination showed significant removal in ammonia and better effluent quality when compared to other control strategies. Practitioner points Developed novel strategies in hierarchical configurations for better nutrient removal with optimal costs in an A2O process. Lower level control strategies deals with dissolved oxygen in last aeration tank and nitrate in fourth anoxic tank (PI/MPC) Higher level control strategy deals with ammonia in the last aeration tank (MPC/Fuzzy). Average and violations of nutrient removal, economy and overall effluent quality for three weather conditions (Dry, Rain and Strom) are studied. A trade‐off is observed between EQI and OCI.

Design of Feedback Control Strategies in a Plant-Wide Wastewater Treatment Plant for Simultaneous Evaluation of Economics, Energy Usage, and Removal of Nutrients

“…Shiek et al (2021) implemented an ammonia-based aeration control (ABAC) with four different combinations of controllers like PI-MPC, MPC-MPC, PI-fuzzy, and MPC-fuzzy, which resulted in a tradeoff between Operational Cost Index (OCI) and EQI. In their study, the ammonia removal rate was improved by 18% in the case of MPC-MPC but P removal was not affected much [23].…”

“…At each control time interval, MPC predicts the nature of the variables of outputs over the prediction horizon (P). The control move sequence is computed over the control horizon (M) based on output predictions [23,45]. A quadratic cost function (Q) is selected for the operation of MPC, which is defined in the mode of Equation (18).…”

“…This is achieved by employing fuzzy rules that are identical to those used in human inference design. FLC is used on the WWTP in this study [19,23]. Figure S4 depicts the FLC controller in the wastewater flow diagram.…”

“…The MF's for both input and output variables are in a Gaussian bell-shaped curve, which is divided into three linguistic variables, "high," "low," and "medium," as shown in Figure 5A,B. A total of three rules are considered according to the S O control loop requirement [23,28].…”

A New Approach to Designing Control of Dissolved Oxygen and Aeration System in Sequencing Batch Reactor by Applied Backstepping Control Algorithm

“…This method was used in the literature [6], where instead of generating a reachable reference trajectory, process performance was optimised using the economic objective function. In the literature [7], the authors proposed a two-level hierarchical control system with the supervisory layer (MPC and Fuzzy) designating the setpoint of the DO concentration based on the ammonia composition and the lower layer controller (proportional-integral [PI]) dealing with DO concentration. Another fuzzy controller in the supervisory layer, which calculates the setpoint of DO concentration and adapts parameters of the lower control layer, was presented in the literature [8].…”