Data Driven Learning and Control seminar series is organized by the Information and Decision Science Lab at Cornell University and aims to explore the latest advancements and interdisciplinary approaches to data-driven learning and control systems.
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Learning-Based Control: Stability, Robustness and Applications
Model-based control has played a vital role in many branches of engineering and sciences. The purpose of this talk is to present a different paradigm for control systems design. Instead of designing controllers from model, we learn desirable controllers directly from data, a new direction in control theory that arises from emerging applications in artificial intelligence and autonomous systems. Learning-based control is a direct control method aimed at developing computationally simple, analytically tractable (reinforcement) learning algorithms with guaranteed stability, robustness and optimality for the closed-loop system. In this talk, I will first review early developments in learning-based control for continuous-time linear and nonlinear systems with unknown dynamics. Then, I will present recent results in robustness of learning-based controllers. Finally, we illustrate the effectiveness of learning-based control via its applications to autonomous vehicles and biological motor control.
Bio: Zhong-Ping Jiang is a professor of electrical and computer engineering at the Tandon School of Engineering, New York University. He received the B.Sc. degree in mathematics from the University of Wuhan in 1988, an M.Sc. degree in statistics from the University of Paris XI in 1989, and his Ph.D. degree in automatic control and mathematics from the ParisTech-Mines (France) in 1993.
Jiang is known for his contributions to stability and control of interconnected nonlinear systems and is a key contributor to nonlinear small-gain theory. His recent research focuses on robust adaptive dynamic programming, learning-based optimal control, nonlinear control, distributed control and optimization, and their applications to computational and systems neuroscience, connected transportation, and cyber-physical-human systems.
Jiang is a deputy editor-in-chief of the IEEE/CAA Journal of Automatica Sinica and has served as senior editor for the IEEE Control Systems Letters (L-CSS), Systems & Control Letters and Journal of Decision and Control, subject editor, associate editor and/or guest editor for several journals including International Journal of Robust and Nonlinear Control, Mathematics of Control, Signals and Systems, IEEE Transactions on Automatic Control, European Journal of Control, and Science China: Information Sciences.