学术报告第201735期

报告题目：Data-Driven Control of Unknown Continuous-time Systems with an Application to Connected Vehicles

报 告 人：Zhong-Ping Jiang, New York University

报告时间：6月26日周一下午15:00

报告地点：南一楼中311室

报告摘要：   In this talk, we present a data-driven control theory for adaptive optimal control design of completely unknown continuous-time systems. Techniques from reinforcement learning, dynamic programming and modern nonlinear control are used to obtain a new class of learning-based adaptive optimal controllers. Then, we show how this data-driven non-model-based control theory can be applied to solve the adaptive optimal control problem for connected autonomous and human-operated vehicles. For simplicity, we consider the scenarios where n human-driven vehicles only transmit motional data and an autonomous vehicle in the tail receives the broadcasted data from preceding vehicles by wireless vehicle-to-vehicle (V2V) communication devices. Considering the cases of range-limited V2V communication and input saturation, several optimal control problems are formulated to minimize the errors of distance and velocity and to optimize the fuel usage. By employing adaptive dynamic programming (ADP) technique, optimal controllers are obtained without relying on the knowledge of system dynamics. Extensions to global nonlinear/adaptive optimal control and adaptive optimal tracking with disturbance rejection are studied. The effectiveness of the proposed approaches is demonstrated via online learning control of connected vehicles in the Paramics’ traffic micro-simulation.

报告人简介：

 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 Ecole des Mines de Paris, France, in 1993.

   Dr. Jiang has been a Professor of Electrical and Computer Engineering at New York University. His main research interests include stability theory, robust/adaptive/distributed nonlinear control, adaptive dynamic programming and their applications to information, mechanical and biological systems. He is coauthor of the books Stability and Stabilization of Nonlinear Systems (with Dr. I. Karafyllis, Springer, 2011), Nonlinear Control of Dynamic Networks (with Drs. T. Liu and D.J. Hill, Taylor & Francis, 2014), and Robust Adaptive Dynamic Programming (with Yu Jiang, IEEE-Wiley, 2017).

   Dr. Jiang is a Senior Editor of IEEE Control Systems Letters, a Deputy co-Editor-in-Chief of the Journal of Control and Decision, an Editor for the International Journal of Robust and Nonlinear Control and has served as an Associate Editor or a Guest Editor for several journals including Mathematics of Control, Signals and Systems (MCSS), Systems & Control Letters, IEEE Transactions on Automatic Control, European Journal of Control, and Science China: Information Sciences. Dr. Jiang is a recipient of the prestigious Queen Elizabeth II Fellowship Award from the Australian Research Council, the CAREER Award from the U.S. National Science Foundation, and the Distinguished Overseas Chinese Scholar Award from the NSF of China. Recent awards recognizing his research work include the Best Theory Paper Award (with Y. Wang) at the 2008 WCICA, and the Guan Zhao Zhi Best Paper Award (with T. Liu and D. Hill) at the 2011 CCC, the Shimemura Young Author Prize (with his student Yu Jiang) at the 2013 Asian Control Conference in Istanbul, Turkey, and the Steve and Rosalind Hsia Best Biomedical Paper Award at the 2016 World Congress on Intelligent Control and Automation in Guilin, China.

    Prof. Jiang is a Fellow of the IEEE and a Fellow of the IFAC.