Linear Operator Theoretic Framework for Data-Driven Optimal Control
Offered By: Fields Institute via YouTube
Course Description
Overview
Explore a 24-minute lecture from the Fourth Symposium on Machine Learning and Dynamical Systems, presented by Umesh Vaidya of Clemson University at the Fields Institute. Delve into the Linear Operator Theoretic Framework for Data-Driven Optimal Control, gaining insights into cutting-edge approaches that merge machine learning techniques with dynamical systems theory. Discover how this framework can be applied to solve complex control problems using data-driven methods, potentially revolutionizing fields such as robotics, autonomous systems, and process control.
Syllabus
Linear Operator Theoretic Framework for Data-Driven Optimal Control:
Taught by
Fields Institute
Related Courses
Underactuated RoboticsMassachusetts Institute of Technology via edX Computer Systems Design for Energy Efficiency
Chalmers University of Technology via edX Differential Equations: 2x2 Systems
Massachusetts Institute of Technology via edX Decision-Making for Autonomous Systems
Chalmers University of Technology via edX Drones and Autonomous Systems I: Fundamentals
University System of Maryland via edX