Real-time Parallelizable Model Predictive Control using Spatio-temporal Splitting

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Event details

Date 11.03.2024
Hour 11:0012:00
Speaker Kristína Fedorová, PhD,  Slovak University of Technology in Bratislava
Location
Category Conferences - Seminars
Event Language English
Abstract: Integrating distributed optimization techniques within a Model Predictive Control (MPC) is a well-established practice in control engineering. In this talk, we will introduce the Real-time Parallelizable Model Predictive Control framework using Spatio-temporal Splitting based on the Augmented Lagrangian-based Alternating Direction Inexact Newton method (ALADIN). We aim to distribute MPC computations across time and space domains concurrently, thereby substantially enhancing computational efficiency. We will delve into the spatial distribution challenges and demonstrate that it is possible to establish a predetermined number of iterations for the proposed algorithm that still guarantees the stabilizable control action while satisfying both input and state constraints. 

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Short bio: Kristína Fedorová is a PhD student at the Department of Information Engineering and Process Control at Slovak University of Technology in Bratislava. She received her Master's degree in Process Control from the Slovak University of Technology in Bratislava. Her research focuses on predictive control and its efficient application in various domains such as power systems, large-scale systems, systems with fast dynamics, and chemical processes