Inexact fast alternating minimization algorithm for distributed model predictive control

  title={Inexact fast alternating minimization algorithm for distributed model predictive control},
  author={Ye Pu and Melanie Nicole Zeilinger and Colin Neil Jones},
  journal={53rd IEEE Conference on Decision and Control},
This paper presents a new distributed optimization technique, the inexact fast alternating minimization algorithm (inexact FAMA), that allows for inexact local computation as well as for errors resulting from limited communication. We show that inexact FAMA is equivalent to the inexact accelerated proximal-gradient method applied to the dual problem and derive an upper-bound on the number of iterations for convergence for inexact FAMA. The second contribution of this work is that a weakened… CONTINUE READING


Publications referenced by this paper.
Showing 1-10 of 19 references

Fast inexact decomposition algorithms for large-scale separable convex optimization

  • Q. T. Dinh, I. Necoara, M. Diehl
  • arXiv preprint arXiv:1212,4275,
  • 2012
1 Excerpt

Convex analysis and monotone operator theory in Hilbert spaces

  • H. H. Bauschke, P. L. Combettes
  • 2011
1 Excerpt

Distributed non-cooperative MPC with neighbor-to-neighbor communication

  • M. Farina, R. Scattolini
  • In 18th World Congress of the International…
  • 2011
1 Excerpt

Similar Papers

Loading similar papers…