从数据中学习非线性系统控制器

IF 7.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Annual Reviews in Control Pub Date : 2023-01-01 DOI:10.1016/j.arcontrol.2023.100915

C. De Persis , P. Tesi

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引用次数: 1

摘要

本文概述了一种利用数据驱动控制为非线性系统设计控制器的新方法。数据驱动控制是控制理论的一个重要研究领域，而这种新方法具有多种优势。它能从以数据为中心的角度重新创建基于模型情况下的许多结果，包括基于泰勒或多项式展开的局部稳定、绝对稳定以及近似和精确反馈线性化。此外，该方法在分析和计算上都很简单，即使在数据被噪声干扰的情况下，也能推断出吸引区域和不变集。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Learning controllers for nonlinear systems from data

This article provides an overview of a new approach to designing controllers for nonlinear systems using data-driven control. Data-driven control is an important area of research in control theory, and this novel method offers several benefits. It can recreate from a data-centred perspective many of the results available in the model-based case, including local stabilization based on Taylor or polynomial expansion, absolute stabilization, as well as approximate and exact feedback linearization. Moreover, the method is analytically and computationally simple, and permits to infer regions of attraction and invariant sets, also when the data are corrupted by noise.

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来源期刊

Annual Reviews in Control 工程技术-自动化与控制系统

CiteScore

19.00

自引率

2.10%

发文量

审稿时长

36 days

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.