Interval Prediction for Continuous-Time Systems with Parametric Uncertainties

被引：0
|
作者：
Leurent, Edouard [1 ]
Efimov, Denis [2 ,3 ]
Raissi, Tarek [4 ]
Perruquetti, Wilfrid [2 ]
机构：
[1] Renault, Paris, France
[2] Univ Lille, INRIA, CNRS, UMR 9189,CRIStAL, F-59000 Lille, France
[3] ITMO Univ, St Petersburg 197101, Russia
[4] Conservatoire Natl Arts & Metiers, Cedric 292, F-75141 Paris, France
来源：
2019 IEEE 58TH CONFERENCE ON DECISION AND CONTROL (CDC) | 2019年
关键词：
LPV SYSTEMS; STATE ESTIMATION; OBSERVERS; DESIGN;
D O I：
10.1109/cdc40024.2019.9029480
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The problem of behaviour prediction for linear parameter-varying systems is considered in the interval framework. It is assumed that the system is subject to uncertain inputs and the vector of scheduling parameters is unmeasurable, but all uncertainties take values in a given admissible set. Then an interval predictor is designed and its stability is guaranteed applying Lyapunov function with a novel structure. The conditions of stability are formulated in the form of linear matrix inequalities. Efficiency of the theoretical results is demonstrated in the application to safe motion planning for autonomous vehicles.
引用
收藏
页码：7049 / 7054
页数：6
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