ECEG 71503 - Data-Driven Models for Control

Three hours lecture. Three credit hours.

This course introduces data-driven models of dynamical systems. The goal is to use statistical and machine learning techniques toward control of complex nonlinear systems. Topics include singular value decomposition for pattern discovery, Fourier and wavelet transform methods, compressed sensing, regression models, data-driven models of dynamical systems, linear control theory, and data-driven control.

Prerequisites: ECEG 5320 or consent of the instructor