Paper Info
Title
Data-Based Receding Horizon Control of Linear Network Systems
Abstract
We propose a distributed data-based predictive control scheme to stabilize a network system described by linear dynamics. Agents cooperate to predict the future system evolution without knowledge of the dynamics, relying instead on learning a data-based representation from a single sample trajectory. We employ this representation to reformulate the finite-horizon Linear Quadratic Regulator problem as a network optimization with separable objective functions and locally expressible constraints. We show that the controller resulting from approximately solving this problem using a distributed optimization algorithm in a receding horizon manner is stabilizing. We validate our results through numerical simulations.
Year
DOI
Venue
2021
10.1109/LCSYS.2020.3021050
IEEE Control Systems Letters
Keywords
DocType
Volume
Data-based control,network systems,predictive control of linear systems
Journal
5
Issue
ISSN
Citations 
4
2475-1456
1
PageRank 
References 
Authors
0.35
0
2
Name
Order
Citations
PageRank
Allibhoy Ahmed110.35
Jorge Cortes21452128.75