Data-driven Control Methods for Civil Engineering

3 credits · Graduate

Introduction to current areas of research at the intersection of machine learning and control with application to civil systems. Investigations of machine learning and data-driven algorithms that interact with the physical world. Topics of study will include learning models of dynamical systems, using these models to represent civil systems, and machine learning techniques to manage and control civil applications spanning from energy systems to water networks, to transportation and supply chains. The course will introduce students to methods to either infer dynamics from data with the goal of using classical control algorithms or develop model-free control strategies starting from data.