School of Information Science and Technology, ShanghaiTech University
Structured nonlinear optimization problems arise in a variety of control applications ranging from nonlinear model predictive control via robust control for uncertain processes to distributed nonlinear control of hybrid systems. Recently, the Augmented Lagrangian based Alternating Direction Inexact Newton (ALADIN) method has been proposed to solve distributed optimization problems. This talk introduces the main idea of ALADIN and its convergence property. After that, it focuses on three applications. The first one is about a real-time variant of ALADIN, which can be used to solve model predictive control problems with long horizons. The second application is about coordinating autonomous vehicles at traffic intersections. The third application is about distributed AC optimal power flow.
Yuning Jiang received the B.S. degree in electronic engineering from Shandong University, Jinan, China, 2014. He is now a Ph.D. candidate supervised by Prof. Boris Houska at ShanghaiTech University. His research interests include distributed optimization and model predictive control, in particular for power flow optimization, intelligent transportation, stochastic control as well as fast MPC algorithms.
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