Robustness margin for piecewise affine explicit control law

Rajesh Koduri 1 Pedro Rodriguez-Ayerbe 1 Sorin Olaru 2, 1
1 L2S - Laboratoire des signaux et systèmes
2 DISCO - Dynamical Interconnected Systems in COmplex Environments
L2S - Laboratoire des signaux et systèmes, Inria Saclay - Ile de France, SUPELEC, CNRS - Centre National de la Recherche Scientifique : UMR8506
Abstract : — Classical robustness margin i.e., gain margin and phase margin, considers the gain variation and phase variation of the model preserving the stability of the closed loop. In this paper, an attempt to find the same kind of margin for a piecewise affine (PWA) controller is done. This controller usually obtained in explicit model predictive control (MPC) is defined over a convex region of the state space X. Starting from the invariance property of the closed loop obtained with a discrete dynamic model and PWA controller in a convex region of the state space, we calculate two robustness margin preserving this invariance property. The first one will be denoted as gain margin corresponding to the variation of the gain of the model guaranteeing the invariance. The second one, that we call, the robustness margin against first order neglected dynamics correspond to the smallest first order neglected dynamic allowed in the system preserving the invariance property.
Type de document :
Communication dans un congrès
55th IEEE Conference on Decision and Control (CDC 2016), Dec 2016, Las Vegas, United States. Decision and Control (CDC), 2016 IEEE 55th Conference on, pp.2327 - 2332, 2016, 〈10.1109/CDC.2016.7798610〉
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https://hal-centralesupelec.archives-ouvertes.fr/hal-01429228
Contributeur : Sorin Olaru <>
Soumis le : samedi 25 mars 2017 - 19:37:48
Dernière modification le : jeudi 26 avril 2018 - 16:26:25
Document(s) archivé(s) le : lundi 26 juin 2017 - 12:12:56

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CENTRALESUPELEC | TDS-MACS | L2S | INRIA | SUP_LSS | UNIV-PARIS-SACLAY | SUP_SYSTEMES

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Rajesh Koduri, Pedro Rodriguez-Ayerbe, Sorin Olaru. Robustness margin for piecewise affine explicit control law. 55th IEEE Conference on Decision and Control (CDC 2016), Dec 2016, Las Vegas, United States. Decision and Control (CDC), 2016 IEEE 55th Conference on, pp.2327 - 2332, 2016, 〈10.1109/CDC.2016.7798610〉. 〈hal-01429228〉

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