Robust Model Predictive Controller for Tracking Changing Periodic Signals

In this paper, we propose a novel robust model predictive controller for tracking periodic signals for linear systems subject to bounded additive uncertainties based on nominal predictions and constraint tightening. The proposed controller joins optimal periodic trajectory planning and robust contro...

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Bibliographic Details
Published inIEEE transactions on automatic control Vol. 62; no. 10; pp. 5343 - 5350
Main Authors Pereira, M., Munoz de la Pena, D., Limon, D., Alvarado, I., Alamo, T.
Format Journal Article
LanguageEnglish
Published IEEE 01.10.2017
Subjects
Closed loop systems
Linear systems
Optimization
Predictive control for linear systems
robust control
Robustness
stability of linear systems
Target tracking
Trajectory
uncertain systems
Uncertainty
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ISSN0018-9286
1558-2523
DOI10.1109/TAC.2016.2636751

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Summary:In this paper, we propose a novel robust model predictive controller for tracking periodic signals for linear systems subject to bounded additive uncertainties based on nominal predictions and constraint tightening. The proposed controller joins optimal periodic trajectory planning and robust control for tracking in a single optimization problem and guarantees that the perturbed closed-loop system converges asymptotically to a neighborhood of an optimal reachable periodic trajectory while robustly satisfying the constraints. In addition, the closed-loop system maintains recursive feasibility even in the presence of sudden changes in the target reference.
ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2016.2636751