Averaging level control for urban drainage system

Abstract

In the work, averaging level control using model-based control and estimation algorithm on a buffer tank system is studied. Implementation of Model Predictive Control (MPC) and Proportional-Integral (PI) control together with Kalman filter for state and disturbance estimation show decent benefits and potentials. Results show that acceptable setpoint tracking of water level in the basin under varying inflow can be achieved. MPC precedes PI for smoother pump actions. Python as a popular programming language is adopted and showed potential for real-time control (RTC).