Robust LQR via bounded data uncertainties

被引：0
|
作者：
Ramos, C. [1 ]
Martínez, M. [1 ]
Sanchis, J. [1 ]
Salcedo, J.V. [1 ]
机构：
[1] Departamento de Ingeniería de Sistemas y Automática, Universidad Politécnica de Valencia, 46022 - Valencia, Camino de Vera s/n
来源：
RIAI - Revista Iberoamericana de Automatica e Informatica Industrial | 2007年 / 4卷 / 03期
关键词：
LQR; Min-Max; Multidimensional systems; Regularization; Riccati matricial equation; Robustness; TPBVP; Uncertainty;
D O I：
10.1016/s1697-7912(07)70225-x
中图分类号：
学科分类号：
摘要：
This work presents the BDU technique (Bounded Data Uncertainties) and the tuning of the linear quadratic regulator (LQR) via this technique, improving the system robustness. The BDU method is stated as a Min-Max problem where the best solution is sought in the worst scenario. So a new LQR tuning method is offered by taking into account the bounds on the uncertainty. The application to multidimensional systems is not trivial since a two-point boundary value problem (TPBVP) appears, which is solved iteratively. Copyright © 2007 CEA-IFAC.
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页码：61 / 72+145
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