Event-triggered model predictive control of wastewater treatment plants

This paper is concerned with the event-triggered model predictive control (ETMPC) problem of nitrogen removal process in the wastewater treatment plants. The main objective of this paper is to design an event-triggered control strategy such that the computation burden can be reduced effectively while maintaining the desired system performance. Unlike existing model predictive control (MPC), the controller in the proposed ETMPC takes action when certain event conditions are satisfied, and thus can reduce the communication and computation resource caused by continuous controller update. The triggering condition is designed according to the system output error and the prediction step of the MPC controller, and thus is easy to check. Moreover, a state space model of the studied nitrogen removal process is built, based on which the ETMPC is designed. The controller is developed to maintain the tracking performance of the dissolved oxygen concentration and nitrate nitrogen concentration by adjusting two key variables in the WWTPs. The stability analysis of the closed-loop system under the designed control strategy is conducted by using the Lyapunov stability theory. Some simulations are conducted to verify the effectiveness of the proposed method. Simulation results show that the proposed method can greatly reduce the number of controller update by up to 60% compared with MPC, whereas the ISE only increases by about 0.1, which is acceptable for WWTPs.