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Journal of Control Science and Engineering
Volume 2012, Article ID 265808, 10 pages
Research Article

Robust MPC with Output Feedback of Integrating Systems

1Cenpes, 21941-915 Rio de Janeiro, RJ, Brazil
2Chemical Engineering Department, University of São Paulo, CP 61548, 05424-970 São Paulo, SP, Brazil
3Chemical Engineering Program/COPPE Federal University of Rio de Janeiro, CP 68502, 21941-970 Rio de Janeiro, RJ, Brazil

Received 27 January 2012; Revised 27 April 2012; Accepted 3 May 2012

Academic Editor: Mohamed Zribi

Copyright © 2012 J. M. Perez et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In this work, it is presented a new contribution to the design of a robust MPC with output feedback, input constraints, and uncertain model. Multivariable predictive controllers have been used in industry to reduce the variability of the process output and to allow the operation of the system near to the constraints, where it is usually located the optimum operating point. For this reason, new controllers have been developed with the objective of achieving better performance, simpler control structure, and robustness with respect to model uncertainty. In this work, it is proposed a model predictive controller based on a nonminimal state space model where the state is perfectly known. It is an infinite prediction horizon controller, and it is assumed that there is uncertainty in the stable part of the model, which may also include integrating modes that are frequently present in the process plants. The method is illustrated with a simulation example of the process industry using linear models based on a real process.