A learning-based approach towards the data-driven predictive control of combined wastewater networks - An experimental study.

Smart control in water systems aims to reduce the cost of infrastructure expansion by better utilizing the available capacity through real-time control. The recent availability of sensors and advanced data processing is expected to transform the view of water system operators, increasing the need for deploying a new generation of data-driven control solutions. To that end, this paper proposes a data-driven control framework for combined wastewater and stormwater networks.

An optimization-based control strategy for energy efficiency of discrete manufacturing systems.

In order to reduce the global energy consumption and avoid highest power peaks during operation of manufacturing systems, an optimization-based controller for selective switching on/off of peripheral devices in a test bench that emulates the energy consumption of a periodic system is proposed. First, energy consumption models for the test-bench devices are obtained based on data and subspace identification methods. Next, a control strategy is designed based on both optimization and receding horizon approach, considering the energy consumption models, operating constraints, and the real processes performed by peripheral devices.

Dynamical tuning for MPC using population games: A water supply network application.

Model predictive control (MPC) is a suitable strategy for the control of large-scale systems that have multiple design requirements, e.g., multiple physical and operational constraints.

Chance-constrained model predictive control applied to inventory management in hospitalary pharmacy.

This extended abstract addresses the preliminary results of applying uncertainty handling strategies and advanced control techniques to the inventary management of hospitality pharmacy. Inventory management is one of the main tasks that a pharmacy department has to carry out in a hospital. It is a complex problem because it requires to establish a tradeoff between contradictory optimization criteria.