Wei Kang: Topics at the Intersection of Deep Learning and Control Theory

Title: Topics at the Intersection of Deep Learning and Control Theory Abstract: Neural networks for control system applications have been studied for decades. During the last few years, research activities focusing on the interplay of deep learning and control theory have attracted increasing attention. In the first part of the talk, we review some selected topics at the intersection of deep learning and control theory, such as how does deep learning help to overcome unmet challenges in control theory? How does control theory help to improve the design and training of neural networks? Why is deep learning able to handle high dimensional models in dynamics and control? In the second part of the talk, we present some theorems and examples from our recent research in which deep neural networks are applied to solve problems of optimal control.