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

9 Citations (Scopus)


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
Number of pages6
ISBN (Electronic)9781479974092
Publication statusPublished - Dec 2014
Event2014 IEEE Conference on Control Applications - Juan Les Antibes, France
Duration: 8 Oct 201410 Oct 2014


Conference2014 IEEE Conference on Control Applications
Abbreviated titleCCA 2014
CityJuan Les Antibes

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering


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

Cite this