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A synthesis framework for robust gain-scheduling controllers

delete2014-11-01
delete35
PRE
AI
J
Joost Veenman *
C
Carsten W. Scherer
DOI:10.1016/j.automatica.2014.10.002delete
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摘要

摘要

En 中文
We present a general framework for the systematic synthesis of robust gain-scheduling controllers by convex optimization techniques and for uncertain dynamical systems described by standard linear fractional representations. We distinguish between linear time-varying parameters, which are assumed to be available online as scheduling parameters for the controller, and genuine uncertainties, not necessarily time-varying, parametric or linear, that are not available online. Under the rough hypothesis that the control channel is not affected by the unmeasurable uncertainties and that the properties of the uncertainties and scheduling variables are captured by suitable families of integral quadratic constraints, this paper reveals how controller synthesis can be turned into a genuine semi-definite program. The design framework is shown to encompass a rich class of concrete scenarios. (C) 2014 Elsevier Ltd. All rights reserved.
Keyword:
Gain-scheduling control
Robust control
Integral quadratic constraints
Convex optimization
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期刊

Automatica 封面图
Automatica
IF:
5.9
论文数:
1.2W
被引数:
5.2W

机构

U
University of Stuttgart
学者数:
1.1W
论文数: 9.4K
被引数: 1.3W
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