Alexandre Sanfelici Bazanella , Lucíola Campestrini , Diego Eckhard
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引用次数: 1
Abstract
A data-driven approach to control design has been developing, since the early 1990’s, upon the concepts and the methods of classical control theory; to this approach we refer as data-driven classical control. This is now a consolidated theory, with a large body of methods and a great number of applications. In this paper we present a survey of these developments along the past three decades. The theory is overviewed, various methods are described, their applications are illustrated and some issues that are sill open for future research are discussed. The extension of these concepts to the design of nonlinear controllers is an emerging and promising subject that is also discussed, and it is shown how it can be approached by the theory of geometric control and the tools of machine learning.
期刊介绍：
The field of Control is changing very fast now with technology-driven “societal grand challenges” and with the deployment of new digital technologies. The aim of Annual Reviews in Control is to provide comprehensive and visionary views of the field of Control, by publishing the following types of review articles:
Survey Article: Review papers on main methodologies or technical advances adding considerable technical value to the state of the art. Note that papers which purely rely on mechanistic searches and lack comprehensive analysis providing a clear contribution to the field will be rejected.
Vision Article: Cutting-edge and emerging topics with visionary perspective on the future of the field or how it will bridge multiple disciplines, and
Tutorial research Article: Fundamental guides for future studies.
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