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SUMMARY:Parallelizable Real-time MPC with ALADIN
DTSTART:20191122T101500
DTEND:20191122T110000
DTSTAMP:20260404T015332Z
UID:748784d98aa3f51858fc0e1d4a1d1fbb915e805ae2bcde393332fa43
CATEGORIES:Conferences - Seminars
DESCRIPTION:Yuning Jiang\nRecently\, the Augmented Lagrangian based Altern
 ating Direction Inexact Newton (ALADIN) method has been proposed to solv
 e distributed optimization problems in control applications. This talk fo
 cuses on the application of ALADIN to solve MPC problems with long horizon
 s and large-scale interconnected systems. First\, we introduce the main i
 dea of ALADIN and its convergence properties for convex and non-convex opt
 imization. Then\, we present a real-time variant for MPC\, which runs a f
 ix number of ALADIN iterations per sampling time. Furthermore\, closed-lo
 op stability is introduced for both the linear and the nonlinear case.\nBi
 o:\nYuning Jiang is a PhD student working with Prof. Boris Houska at the 
 School of Information Science and Technology at ShanghaiTech University.\n
 His research focuses on distributed optimization and model predictive cont
 rol.
LOCATION:ME C2 405 https://plan.epfl.ch/?room==ME%20C2%20405
STATUS:CONFIRMED
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