###### Abstract  
This paper addresses the implementation of economic-oriented model predictive controllers for the dynamic real-time optimization of the operation of wastewater treatment plants (WWTP). Both the economic-optimizing controller (pure-EMPC) and the economic-oriented tracking controller (Hybrid-EMPC, or HEMPC) formulations are validated in the benchmark simulation model (BSM1) platform that represents the behavior of a characteristic activated sludge process. The objective of the controllers is to ensure the appropriate operation of the plant, while minimizing the energy consumption and the fines for violations of the limits of the ammonia concentration in the effluent along the full operating period. A non-linear reduced model of the activated sludge process is used for predictions to obtain a reasonable computing effort, and techniques to deal with model-plant mismatch are incorporated in the controller algorithm. Different designs and structures are compared in terms of process performance and energy costs, which show that the implementation of the proposed control technique can produce significant economic and environmental benefits, depending on the desired performance criteria. w _Applied_  
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A detailed description of the developments of instrumentation and control systems for WWTPs can be found in [PERSON] [2]. [PERSON] et al. [5] present a complete review of the aeration control strategies considering instrumentation, control algorithms, and even a description of the aeration system. They report that the most usual control solutions in the different WWTP control loops are based on simple proportional integral (PI) controllers. Even the derivative term is rarely used in practice [2]. These PI-based control loops (aeration, nitrate recirculation, cascade ammonia control, etc.) are usually based on regulation of the key variables at a constant set point. The benefits of advanced control techniques, such as model predictive control (MPC) for optimizing the operation of WWTPs, are pointed out in [PERSON] et al. [3] and [PERSON] et al. [5]; interesting applications are found in [6; 7]. Due to the demand for solutions to improve the efficiency of WWTPs, particular attention is being paid to the application of real-time optimization systems (RTOs) [8; 9; 10; 11; 12]. The typical RTOs are hierarchical control structures that carry out the economic optimization of the set points in an upper level and send them the basic control level [13; 14]. Recently, the single-layer economic model predictive control strategy has emerged as an alternative to the hierarchical RTO to perform the dynamic optimization of the operation improving the effluent quality and the economic performance [15; 16]. The economic-oriented model predictive controller (EMPC) approaches include economic objectives in the cost function of the standard model predictive control (MPC) algorithm. It can be used as an optimizer in a hierarchical structure, or directly in the control level, combining the optimization and control tasks in the same algorithm [17]. The implementation directly in the control level is promising, since the algorithm is able to capture the impact of fast disturbances over plant behavior and process economics, thus providing the optimal control inputs, accounting for process restrictions [18]. Moreover, the use of single-layer structures reduces the computational effort, avoids communication problems between layers, and also avoids the use of different models in the optimization and control levels [13; 19]. All of these characteristics make the single-layer EMPC an interesting solution to attain an adequate compromise between energy costs and effluent quality in the operation of WWTPs. The non-linear EMPCs have been successfully applied both in WWTPs in the upper layer of a hierarchical structure [8; 9], and directly in the control level [15; 16].