Journal article

Optimal move blocking strategies for model predictive control

Rohan C Shekhar, Chris Manzie

Automatica | PERGAMON-ELSEVIER SCIENCE LTD | Published : 2015


This paper presents a systematic methodology for designing move blocking strategies to reduce the complexity of a model predictive controller for linear systems, with explicit optimisation of the blocking structure using mixed-integer programming. Given a move-blocked predictive controller with a terminal invariant set constraint for stability, combined with an input parameterisation to preserve recursive feasibility, two different optimisation problems are formulated for blocking structure selection. The first problem calculates the maximum achievable reduction in the number of input decision variables and prediction horizon length, subject to the controller's region of attraction containin..

View full abstract


Awarded by Australian Research Council's Discovery Projects funding scheme

Funding Acknowledgements

This work was supported under the Australian Research Council's Discovery Projects funding scheme (Project DP120101830). The material in this paper was not presented at any conference. This paper was recommended for publication in revised form by Associate Editor Lalo Magni under the direction of Editor Ian R. Petersen.