Speaker
Description
Control theory is a pivotal field of study that focuses on the behavior of dynamical systems and the development of strategies to influence these systems towards desired outcomes. The principle of control theory find its application in plenty of disciplines including engineering, economics, biology and beyond. It were control concepts like the Kalman filter that has flew the Apollo to the moon. Also for the operation of particle accelerator there are thousands of control loops running, ranging from low-level hardware-focused systems, as magnet powering, synchronization or RF control, over fast transverse feedback systems to beam steering.
In this tutorial, we begin by exploring the basic concepts of control, emphasizing the importance of stability and robustness. The tutorial then introduces the mathematical modeling of systems using differential equations and the representation of these systems in state-space form. Starting from classical control strategies, we will go towards modern optimal control techniques and will finally see the link to optimization and ML approaches like reinforcement learning.
