Application of neural networks for optimal-setpoint design and MPC control in biological wastewater treatment

作者：Sadeghassadi Mahsa^*; Macnab Chris J B; Gopaluni Bhushan; Westwick David

来源：Computers & Chemical Engineering, 2018, 115: 150-160.

DOI：10.1016/j.compchemeng.2018.04.007

• BSM1
• Neural network control
• Model predictive control
• Biological wastewater treatment

This paper addresses both the design of an optimal variable setpoint and a setpoint-tracking control loop for the dissolved oxygen concentration in a biological wastewater treatment process. Although exact knowledge of influent changes during rain/storm events is unrealistic, we take advantage of the fact that during dry weather conditions the influent changes are periodic and thus predictable. Specifically, a nonlinear optimization procedure utilizes dry weather data to decide on a nominal fixed setpoint, or a weighting gain, or both; during weather events an algorithm uses the optimization solution(s) together with the ammonium predictions to adjust the setpoint dynamically (responding appropriately to significant changes in the influent). A constrained nonlinear neural-network model predictive control tracks the setpoint. Simulations with the BSM1 compare several variations of the proposed methods to a fixed-setpoint PI control, demonstrating improvement in effluent quality or reduction in energy use, or both.

• 出版日期2018-7-12