Robust-Adaptive Interval Predictive Control for Linear Uncertain Systems

被引：0
|
作者：
Leurent, Edouard [1 ]
Efimov, Denis [2 ,3 ,4 ]
Maillard, Odalric-Ambrym [2 ,3 ,4 ]
机构：
[1] Renault Grp, Paris, France
[2] Inria Valse, Villeneuve Dascq, France
[3] Inria SequeL, Villeneuve Dascq, France
[4] Inria Lille Nord Europe, Villeneuve Dascq, France
来源：
2020 59TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC) | 2020年
关键词：
STABILITY; OBSERVER;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：1429 / 1434
页数：6
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