📝 SummarXiv

Abstract

We design a model-predictive controller for managing the actuators in sewer networks. It minimizes flooding and combined-sewer overflow during rain and pollution at other times. To make the problem tractable, we use a convex relaxation of the microbial growth kinetics and a physically motivated linearization of the mass flow bilinearities. With these approximations, the trajectory optimization in each control period is a second-order cone program. In simulation, the controller releases roughly 15% less pollutant mass than a conventional controller while treating nearly the same volume of flow. It does so by better balancing the flow over the treatment plants and over time.