AutoDDC: Hyperparameter Tuning for Direct Data-Driven Control

被引：1
|
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
收藏
页码：98 / 124
页数：27
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