AutoDDC: Hyperparameter Tuning for Direct Data-Driven Control

被引：4

作者：

Breschi, Valentina ^{[1
]}

Formentin, Simone ^{[2
]}

机构：

[1] Eindhoven Univ Technol, NL-5600 MB Eindhoven, Netherlands

[2] Politecn Milan, I-20133 Milan, Italy

来源：

IEEE CONTROL SYSTEMS MAGAZINE | 2023年 / 43卷 / 06期

关键词：

Tuning; Predictive control; Calibration; Optimization methods; Behavioral sciences; Costs; Predictive models; Control systems; Control design; Hyperparameter optimization; MODEL-REFERENCE CONTROL; CONTROL DESIGN; IDENTIFICATION; VEHICLES; VRFT;

D O I：

10.1109/MCS.2023.3310368

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In many control applications, model-based design has become the standard practice due to the obvious advantages of a convenient, understandable description of the process and the possibility of a continuous validation of the controlled system at all stages of development [1].

引用

页码：98 / 124

页数：27

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