Control and Optimization with Applications in Robotics

Catalog description

This course covers a variety of advanced topics in model-based nonlinear control, primarily focused on computational techniques and dynamic robotic applications. Students will learn both the theoretical basics of nonlinear and optimal control along with computational algorithms. Topics include dynamic programming, trajectory optimization, canonical underactuated systems, control of limit cycles, stability analysis, nonsmooth mechanics, and model predictive control. Applications include walking and running robots, manipulation, and flying machines. As the course will cover state of the art techniques, we will review relevant research papers. At the end of the semester, students will prepare and present a final project on a related topic of their choosing. Prerequisite: If course requirement not met, permission of instructor required.