Data-driven Systems and Controls: 16:332:514:01
Course instructor: Daniel Burbano (email address: daniel.burbano@rutgers.edu)
Learning objectives:
This course is designed to provide students with comprehensive knowledge of various data-driven techniques for addressing practical challenges in dynamic systems and controls. The learning journey begins with a solid foundation in linear dynamic system modeling, encompassing both continuous and discrete-time representations, along with feedback control strategies. Students will then learn to reverse engineer linear models directly from data, stabilizing linear systems using data-driven approaches, and designing optimal controllers informed by data. In addition, students will learn more advanced topics, including model-free control techniques such as model-predictive control, extremum-seeking, and machine-learning control.
Pre-Requisite: Students should be familiar with differential equations (01:640:252) and matrix/vector analysis (01:640:250).
More info: https://www.ece.rutgers.edu/graduate-courses