Dengfeng Sun, of Purdue University, presented A Computational Optimization Method in Networked Dynamical Systems under Uncertainties on Feb. 1, 2019 t 4 p.m. in 290 Hearst Memorial Minng Building.
Abstract
Most research in control and optimization of networked dynamical systems heavily relies on the fidelity of the dynamics models and efficient computational techniques to execute optimized control actions, while many autonomous systems are inherently subject to uncertainties and disturbances. This talk will present some of our recent research in modeling, optimization, and computation algorithms and tools that can efficiently handle uncertainties in large-scale autonomous systems using the national air transportation system as an example. In this research, a data-driven approach is developed for a networked dynamical system model, which formulates probabilistic constraints to consider system uncertainties. In order to efficiently solve such a large-scale chance-constrained problem, a convex approximation approach is developed, which takes advantages of and addresses the challenges in modern convex optimization techniques in solving nonlinear stochastic control and optimization problems. This algorithm is mathematically and experimentally proved to converge to an optimal solution in polynomial time.
Presenter
Dengfeng Sun is an Associate Professor in School of Aeronautics and Astronautics at Purdue University, West Lafayette, Indiana. Before joining Purdue, he was an Associate Scientist with University of California Santa Cruz at NASA Ames Research Center. He received a bachelor's degree in precision instruments and mechanology from Tsinghua University in China, a master's degree in industrial and systems engineering from the Ohio State University, and a PhD degree in systems engineering from University of California at Berkeley. Dr. Sun is a Senior Member of American Institute of Aeronautics and Astronautics (AIAA). He is on the AIAA's Guidance, Navigation, and Control Technical Committee, and serves as a Co-Director of the Federal Aviation Administration’s Consortium in Aviation Operations Research (NEXTOR II) and an Associate Editor of IEEE Transactions on Intelligent Transportation Systems. Dr. Sun's research interests include control and optimization of large scale systems and their applications in aerospace engineering. He is a private pilot and advises Purdue Pilots, Inc. (PPI), a student-run flying club at Purdue University.