Data-Driven Gain Scheduling Control of Linear Parameter-Varying Systems Using Quadratic Matrix Inequalities

被引：10
|
作者：
Miller, Jared [1 ]
Sznaier, Mario [1 ]
机构：
[1] Northeastern Univ, ECE Dept, Robust Syst Lab, Boston, MA 02115 USA
来源：
IEEE CONTROL SYSTEMS LETTERS | 2023年 / 7卷
关键词：
Data-driven control; linear parameter-varying systems; LMIs; numerical algorithms;
D O I：
10.1109/LCSYS.2022.3227182
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This letter synthesizes a gain-scheduled controller to stabilize all possible Linear Parameter-Varying (LPV) plants that are consistent with measured input/state data records. Inspired by prior work in data informativity and LTI stabilization, a set of Quadratic Matrix Inequalities is developed to represent the noise set, the class of consistent LPV plants, and the class of stabilizable plants. The bilinearity between unknown plants and 'for all' parameters is avoided by vertex enumeration of the parameter set. Effectiveness and computational tractability of this method is demonstrated on example systems.
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页码：835 / 840
页数：6
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