KON 447E - Data Driven Control

Course Objectives

I. To teach the basic concepts of data-driven control systems.
II. To provide the application of machine learning algorithms to control engineering problems.
III. To provide students with data collection and analysis competence for system identification, state estimation and control design.
IV. To teach data-driven modeling methods such as support vector machines and neural networks.
V. To provide students with the ability to apply machine learning-based solutions in modern control systems.

Course Description

Traditional and data-driven control, singular value decomposition, sparsity and compressed sensing, regression, model selection, clustering and classification, support vector machines, neural networks and deep learning, extreme learning machines, data-driven dynamical systems, dynamic mode decomposition, sparse identification, koopman operator theory, data-driven koopman analysis, data-driven control