Robust-Adaptive Interval Predictive Control ...
Document type :
Communication dans un congrès avec actes
Title :
Robust-Adaptive Interval Predictive Control for Linear Uncertain Systems
Author(s) :
Leurent, Edouard [Auteur]
RENAULT
Efimov, Denis [Auteur]
Centrale Lille
Centre National de la Recherche Scientifique [CNRS]
Université de Lille
Finite-time control and estimation for distributed systems [VALSE]
Maillard, Odalric Ambrym [Auteur]
Centrale Lille
Centre National de la Recherche Scientifique [CNRS]
Université de Lille
Scool [Scool]
Sequential Learning [SEQUEL]
RENAULT
Efimov, Denis [Auteur]

Centrale Lille
Centre National de la Recherche Scientifique [CNRS]
Université de Lille
Finite-time control and estimation for distributed systems [VALSE]
Maillard, Odalric Ambrym [Auteur]

Centrale Lille
Centre National de la Recherche Scientifique [CNRS]
Université de Lille
Scool [Scool]
Sequential Learning [SEQUEL]
Conference title :
CDC 2020 - 59th IEEE Conference on Decision and Control
City :
Jeju Island / Virtual
Country :
Corée du Sud
Start date of the conference :
2020-12-10
HAL domain(s) :
Sciences de l'ingénieur [physics]/Automatique / Robotique
English abstract : [en]
We consider the problem of stabilization of a linear system, under state and control constraints, and subject to bounded disturbances and unknown parameters in the state matrix. First, using a simple least square solution ...
Show more >We consider the problem of stabilization of a linear system, under state and control constraints, and subject to bounded disturbances and unknown parameters in the state matrix. First, using a simple least square solution and available noisy measurements, the set of admissible values for parameters is evaluated. Second, for the estimated set of parameter values and the corresponding linear interval model of the system, two interval predictors are recalled and an unconstrained stabilizing control is designed that uses the predicted intervals. Third, to guarantee the robust constraint satisfaction, a model predictive control algorithm is developed, which is based on solution of an optimization problem posed for the interval predictor. The conditions for recursive feasibility and asymptotic performance are established. Efficiency of the proposed control framework is illustrated by numeric simulations.Show less >
Show more >We consider the problem of stabilization of a linear system, under state and control constraints, and subject to bounded disturbances and unknown parameters in the state matrix. First, using a simple least square solution and available noisy measurements, the set of admissible values for parameters is evaluated. Second, for the estimated set of parameter values and the corresponding linear interval model of the system, two interval predictors are recalled and an unconstrained stabilizing control is designed that uses the predicted intervals. Third, to guarantee the robust constraint satisfaction, a model predictive control algorithm is developed, which is based on solution of an optimization problem posed for the interval predictor. The conditions for recursive feasibility and asymptotic performance are established. Efficiency of the proposed control framework is illustrated by numeric simulations.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
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