Robust-Adaptive Interval Predictive Control for Linear Uncertain Systems - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year :

Robust-Adaptive Interval Predictive Control for Linear Uncertain Systems


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.


Fichier principal
Vignette du fichier
CDC20_Edouard.pdf (435.34 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-02942414 , version 1 (17-09-2020)


  • HAL Id : hal-02942414 , version 1


Edouard Leurent, Denis Efimov, Odalric-Ambrym Maillard. Robust-Adaptive Interval Predictive Control for Linear Uncertain Systems. CDC 2020 - 59th IEEE Conference on Decision and Control, Dec 2020, Jeju Island / Virtual, South Korea. ⟨hal-02942414⟩
72 View
142 Download


Gmail Facebook Twitter LinkedIn More