Artificial Intelligence for Control of Environmental Systems

3.0 credits · Graduate

The course has the dual objective of introducing students to the control problems characterizing modern environmental and water infrastructures while exposing them to real-world examples of how modelling and control analytics are used. Specific topics include: (1) dynamic programming and its main extensions (stochastic and approximate DP), (2) policy search for single- and multi-objective problems, (3) deterministic and stochastic model predictive control, (4) model-order reduction and its application to large-scale control problems. Emphasis will be given not only to the theoretical aspects underpinning the control problems, but also to their practical use. Examples will be drawn from several domains, including reservoir operations, urban water supply, drainage networks, and groundwater management. Emphasis will be also placed on the role that data analysis plays in the formulation of these control problems. Class periods will be a mixture of in-person lectures, group discussions, and hands-on activities.