D-ADMM based distributed MPC with input-output models

Rafael P. Costa, João M. Lemos, João F. C. Mota, João M. F. Xavier

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

This article presents a distributed model predictive controller (MPC) based on linear models that use input/output plant data and D-ADMM optimization. The use of input/output models has the advantage of not requiring a Kalman filter to estimate the plant state. The D-ADMM algorithm solves the optimization problem associated to a cost function that is the sum of the control agents private costs, being a modification of the Alternating Direction of Multipliers (ADMM) algorithm that requires no central node and implies a significant reduction in the communication among adjacent nodes. The distributed MPC is obtained for the special case of a linear graph. An application to distributed control of a water delivery canal is presented to illustrate the algorithm.

Original languageEnglish
Title of host publication2014 IEEE Conference on Control Applications, CCA 2014
PublisherIEEE
Pages699-704
Number of pages6
ISBN (Electronic)9781479974092
DOIs
Publication statusPublished - Dec 2014
Event2014 IEEE Conference on Control Applications - Juan Les Antibes, France
Duration: 8 Oct 201410 Oct 2014

Conference

Conference2014 IEEE Conference on Control Applications
Abbreviated titleCCA 2014
CountryFrance
CityJuan Les Antibes
Period8/10/1410/10/14

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering

Fingerprint Dive into the research topics of 'D-ADMM based distributed MPC with input-output models'. Together they form a unique fingerprint.

  • Cite this

    Costa, R. P., Lemos, J. M., Mota, J. F. C., & Xavier, J. M. F. (2014). D-ADMM based distributed MPC with input-output models. In 2014 IEEE Conference on Control Applications, CCA 2014 (pp. 699-704). [6981422] IEEE. https://doi.org/10.1109/CCA.2014.6981422