Combining learning and control in linear systems

IF 2.5 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS European Journal of Control Pub Date : 2024-11-01 DOI:10.1016/j.ejcon.2024.101043
Andreas A. Malikopoulos
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Abstract

In this paper, we provide a theoretical framework that separates the control and learning tasks in a linear system. This separation allows us to combine offline model-based control with online learning approaches and thus circumvent current challenges in deriving optimal control strategies in applications where a large volume of data is added to the system gradually in real time and not altogether in advance. We provide an analytical example to illustrate the framework.
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线性系统中的学习与控制相结合
在本文中,我们提供了一个理论框架,将线性系统中的控制和学习任务分离开来。这种分离使我们能够将基于模型的离线控制与在线学习方法结合起来,从而规避当前在推导最优控制策略方面所面临的挑战,因为在这种应用中,大量数据是实时逐步添加到系统中的,而不是事先完全添加到系统中的。我们提供了一个分析示例来说明该框架。
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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来源期刊
European Journal of Control
European Journal of Control 工程技术-自动化与控制系统
CiteScore
5.80
自引率
5.90%
发文量
131
审稿时长
1 months
期刊介绍: The European Control Association (EUCA) has among its objectives to promote the development of the discipline. Apart from the European Control Conferences, the European Journal of Control is the Association''s main channel for the dissemination of important contributions in the field. The aim of the Journal is to publish high quality papers on the theory and practice of control and systems engineering. The scope of the Journal will be wide and cover all aspects of the discipline including methodologies, techniques and applications. Research in control and systems engineering is necessary to develop new concepts and tools which enhance our understanding and improve our ability to design and implement high performance control systems. Submitted papers should stress the practical motivations and relevance of their results. The design and implementation of a successful control system requires the use of a range of techniques: Modelling Robustness Analysis Identification Optimization Control Law Design Numerical analysis Fault Detection, and so on.
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