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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Journal ArticleDOI
Big Data for Modern Industry: Challenges and Trends [Point of View]
Shen Yin,Okyay Kaynak +1 more
TL;DR: In this article, the authors explore ways in business and industry is working to manage data and reports on applications that support these initiatives, and report on how they can be used in the context of big data.
Journal ArticleDOI
State of Charge Estimation for Lithium-Ion Batteries Using Model-Based and Data-Driven Methods: A Review
TL;DR: This review presents the recent SOC estimation methods highlighting the model-based and data-driven approaches and delivers potential recommendations for the development of SOC estimation method of lithium-ion battery in EV applications.
Journal ArticleDOI
On Model-Free Adaptive Control and Its Stability Analysis
TL;DR: The theoretical analysis of the bounded-input bounded-output stability, the monotonic convergence of the tracking error dynamics, and the internal stability of the full form dynamic linearization based MFAC scheme are rigorously presented by the contraction mapping principle.
Journal ArticleDOI
An Overview of Dynamic-Linearization-Based Data-Driven Control and Applications
TL;DR: This work highlights the characteristics and comments of the different model-free adaptive control schemes in detail to facilitate the understanding of the readers.
Posted Content
Formulas for Data-driven Control: Stabilization, Optimality and Robustness
Claudio De Persis,Pietro Tesi +1 more
TL;DR: A parametrization of linear feedback systems is derived that paves the way to solve important control problems using data-dependent linear matrix inequalities only and is remarkable in that no explicit system's matrices identification is required.
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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