Journal ArticleDOI
From model-based control to data-driven control: Survey, classification and perspective
Zhongsheng Hou,Zhuo Wang +1 more
TLDR
This paper is a brief survey on the existing problems and challenges inherent in model-based control (MBC) theory, and some important issues in the analysis and design of data-driven control (DDC) methods are here reviewed and addressed.About:
This article is published in Information Sciences.The article was published on 2013-06-01. It has received 828 citations till now.read more
Citations
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Book ChapterDOI
Summarisation and Relevance Evaluation Techniques for Big Data Exploration: The Smart Factory Case Study
TL;DR: This paper proposes an approach to support and ease exploration of real time data in a dynamic context of interconnected systems, such as the Industry 4.0 domain, where large amounts of data must be incrementally collected, organized and analysed on-the-fly.
Journal ArticleDOI
Distributed adaptive optimal regulation of uncertain large-scale interconnected systems using hybrid Q-learning approach
TL;DR: In this paper, a hybrid Q-learning algorithm is introduced for the design of a linear adaptive optimal regulator for a large-scale interconnected system with event-sampled inputs and state vector.
Journal ArticleDOI
Dissipativity learning control (DLC): A framework of input–output data-driven control
Wentao Tang,Prodromos Daoutidis +1 more
TL;DR: A dissipativity learning control framework which involves the data-based learning of the dissipativity property of the control system, followed by a dissipativity-based controller design procedure is proposed.
Journal ArticleDOI
Event-triggered distributed coordinated control of networked autonomous surface vehicles subject to fully unknown kinetics via concurrent-learning-based neural predictor
TL;DR: Simulation results are provided to demonstrate the effectiveness of the proposed distributed coordinated control for networked ASVs by using event-triggered mechanisms and concurrent-learning-based neural predictors.
References
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Book
System Identification: Theory for the User
TL;DR: Das Buch behandelt die Systemidentifizierung in dem theoretischen Bereich, der direkte Auswirkungen auf Verstaendnis and praktische Anwendung der verschiedenen Verfahren zur IdentifIZierung hat.
Book ChapterDOI
A New Approach to Linear Filtering and Prediction Problems
TL;DR: In this paper, the clssical filleting and prediclion problem is re-examined using the Bode-Shannon representation of random processes and the?stat-tran-sition? method of analysis of dynamic systems.
Journal ArticleDOI
Machine learning
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Journal ArticleDOI
Technical Note : \cal Q -Learning
Chris Watkins,Peter Dayan +1 more
TL;DR: This paper presents and proves in detail a convergence theorem forQ-learning based on that outlined in Watkins (1989), showing that Q-learning converges to the optimum action-values with probability 1 so long as all actions are repeatedly sampled in all states and the action- values are represented discretely.
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