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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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 |
_version_ |
1725107413495840768 |