IRI - Constrained distributed optimization: A population dynamics approach

Publication

Constrained distributed optimization: A population dynamics approach

Journal Article (2016)

Journal

Automatica

Pages

101-116

Volume

Number

2016

Doc link

http://dx.doi.org/10.1016/j.automatica.2016.02.004

File

Download the digital copy of the doc pdf document

Authors

Projects associated

ECOCIS: EConomic Operation of Critical Infrastructure Systems

Abstract

Large-scale network systems involve a large number of states, which makes the design of real-time controllers a challenging task. A distributed controller design allows to reduce computational requirements since tasks are divided into different systems, allowing real-time processing. This paper proposes a novel methodology for solving constrained optimization problems in a distributed way inspired by population dynamics. This methodology consists of an extension of a population dynamics equation and the introduction of a mass dynamics equation. The proposed methodology divides the problem into smaller sub-problems, whose feasible regions vary over time achieving an agreement to solve the global problem. The methodology also guarantees attraction to the feasible region and allows to have few changes in the decision-making design when a network suffers the addition/removal of nodes/edges. Then, distributed controllers are designed with the proposed methodology and applied to the large-scale Barcelona Drinking Water Network (BDWN). Some simulations are presented and discussed in order to illustrate the control performance.

Author keywords

distributed optimization, evolutionary game theory, large-scale systems

Scientific reference

J. Barreiro-Gomez, N. Quijano and C. Ocampo-Martínez. Constrained distributed optimization: A population dynamics approach. Automatica, 69(2016): 101-116, 2016.