Off-line robustification of Generalized Predictive Control for uncertain systems

An off-line methodology was proposed for enhancing the robustness of an initial Generalized Predictive Control (GPC) by convex optimization of the Youla parameter. However, this procedure of robustification is restricted with the case of the systems affected only by unstructured uncertainties. This...

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Main Authors: Khelifi Otmane Khelifa, Bali Nordine, Nezli Lazhari
Format: Article
Language:English
Published: Polish Academy of Sciences 2014-12-01
Series:Archives of Control Sciences
Subjects:
Online Access:http://www.degruyter.com/view/j/acsc.2014.24.issue-4/acsc-2014-0027/acsc-2014-0027.xml?format=INT
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spelling doaj-6f9842c5c67a4cf1ba72e4589c6e94d82020-11-25T01:27:01ZengPolish Academy of SciencesArchives of Control Sciences2300-26112014-12-0124449951310.2478/acsc-2014-0027acsc-2014-0027Off-line robustification of Generalized Predictive Control for uncertain systemsKhelifi Otmane Khelifa0Bali Nordine1Nezli Lazhari2Process Control Laboratory, Ecole Nationale Polytechnique, ENP, AlgersProcess Control Laboratory, Ecole Nationale Polytechnique, ENP, AlgersIndustrial Systems Laboratory, University of Sciences and Technology Houari Boumediene, AlgiersAn off-line methodology was proposed for enhancing the robustness of an initial Generalized Predictive Control (GPC) by convex optimization of the Youla parameter. However, this procedure of robustification is restricted with the case of the systems affected only by unstructured uncertainties. This paper proposes an extension of this method to the systems subjected to both unstructured and structured polytopic uncertainties. The main idea consists in adding supplementary constraints to the optimization problem which validates the Lipatov stability condition at each vertex of the polytope. These polytopic uncertainties impose a set of non convex quadratic constraints. The globally optimal solution is found by means of the GloptiPoly3 software. Therefore, this robustification provides stability robustness towards unstructured uncertainties for the nominal system, while guaranteeing stability properties over a specified polytopic domain of uncertainties. Finally, an illustrative example is givenhttp://www.degruyter.com/view/j/acsc.2014.24.issue-4/acsc-2014-0027/acsc-2014-0027.xml?format=INTGeneralized Predictive Controlpolytopic uncertaintiesrelaxationrobust controlYoula parametrization
collection DOAJ
language English
format Article
sources DOAJ
author Khelifi Otmane Khelifa
Bali Nordine
Nezli Lazhari
spellingShingle Khelifi Otmane Khelifa
Bali Nordine
Nezli Lazhari
Off-line robustification of Generalized Predictive Control for uncertain systems
Archives of Control Sciences
Generalized Predictive Control
polytopic uncertainties
relaxation
robust control
Youla parametrization
author_facet Khelifi Otmane Khelifa
Bali Nordine
Nezli Lazhari
author_sort Khelifi Otmane Khelifa
title Off-line robustification of Generalized Predictive Control for uncertain systems
title_short Off-line robustification of Generalized Predictive Control for uncertain systems
title_full Off-line robustification of Generalized Predictive Control for uncertain systems
title_fullStr Off-line robustification of Generalized Predictive Control for uncertain systems
title_full_unstemmed Off-line robustification of Generalized Predictive Control for uncertain systems
title_sort off-line robustification of generalized predictive control for uncertain systems
publisher Polish Academy of Sciences
series Archives of Control Sciences
issn 2300-2611
publishDate 2014-12-01
description An off-line methodology was proposed for enhancing the robustness of an initial Generalized Predictive Control (GPC) by convex optimization of the Youla parameter. However, this procedure of robustification is restricted with the case of the systems affected only by unstructured uncertainties. This paper proposes an extension of this method to the systems subjected to both unstructured and structured polytopic uncertainties. The main idea consists in adding supplementary constraints to the optimization problem which validates the Lipatov stability condition at each vertex of the polytope. These polytopic uncertainties impose a set of non convex quadratic constraints. The globally optimal solution is found by means of the GloptiPoly3 software. Therefore, this robustification provides stability robustness towards unstructured uncertainties for the nominal system, while guaranteeing stability properties over a specified polytopic domain of uncertainties. Finally, an illustrative example is given
topic Generalized Predictive Control
polytopic uncertainties
relaxation
robust control
Youla parametrization
url http://www.degruyter.com/view/j/acsc.2014.24.issue-4/acsc-2014-0027/acsc-2014-0027.xml?format=INT
work_keys_str_mv AT khelifiotmanekhelifa offlinerobustificationofgeneralizedpredictivecontrolforuncertainsystems
AT balinordine offlinerobustificationofgeneralizedpredictivecontrolforuncertainsystems
AT nezlilazhari offlinerobustificationofgeneralizedpredictivecontrolforuncertainsystems
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