Jorge Cortés
Professor
Cymer Corporation Endowed Chair
Data-based receding horizon control of linear
network systems
A. Allibhoy, J. Cortés
IEEE Control Systems Letters 5 (4) (2021), 1207-1212
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.
pdf
Mechanical and Aerospace Engineering,
University of California, San Diego
9500 Gilman Dr,
La Jolla, California, 92093-0411
Ph: 1-858-822-7930
Fax: 1-858-822-3107
cortes at ucsd.edu
Skype id:
jorgilliyo