Ezra Systems Seminar: Zhong-Ping Jiang (NYU)

Description

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The Nonlinear Small-Gain Theory for Networks and Control

The world is nonlinear and linked. Small-gain theory is one of the most important tools to tackle fundamentally challenging control problems for interconnected linear and nonlinear systems. In this talk, I will first review early developments in nonlinear small-gain theorems and associated nonlinear control design and show how it served as a basic tool to unify numerous results in constructive nonlinear control. Then, I will present recent developments in network/cyclic small-gain theorems for complex large-scale nonlinear systems, with a special focus on event-triggered control and feedback optimization. Finally, I will discuss briefly how machine learning techniques can be invoked to relax the conservativeness of small-gain designs, that falls into the emerging area of learning-based control, a new direction in control theory.

Bio: Zhong-Ping Jiang received the B.Sc. degree in mathematics from the University of Wuhan, Wuhan, China, in 1988, the M.Sc. degree in statistics from the University of Paris XI, France, in 1989, and the Ph.D. degree in automatic control and mathematics from the ParisTech-Mines, France, in 1993, under the direction of Prof. Laurent Praly.

Currently, he is a professor of electrical and computer engineering at the Tandon School of Engineering at New York University. He is known for fundamental contributions to nonlinear control theory and applications. In particular, he is a key contributor to nonlinear small-gain theory. His main research interests include stability theory, robust/adaptive/distributed nonlinear control, adaptive dynamic programming and their applications to information, mechanical and biological systems.

Prof. Jiang is a Fellow of IEEE, IFAC and CAA. and is among the Clarivate Analytics Highly Cited Researchers.