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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Proceedings Article
Data-Driven Controller Synthesis of Unknown Nonlinear Polynomial Systems via Control Barrier Certificates
TL;DR: A data-driven approach to synthesize safety controllers for continuous-time nonlinear polynomial-type systems with unknown dynamics based on notions of so-called control barrier certificates constructed from data while providing a guaranteed confidence of 1 on the safety of unknown systems.
Journal ArticleDOI
A Dynamic Linearization Modeling of Thermally Induced Error Based on Data-Driven Control for CNC Machine Tools
TL;DR: The feasibility and effectiveness of the proposed dynamic linearization modeling method has been verified using two experiments, demonstrating excellent robustness and ability to adapt to various machining conditions and to improve machining accuracy.
Journal ArticleDOI
A center manifold theory-based approach to the stability analysis of state feedback takagi-sugeno-kang fuzzy control systems
Radu-Emil Precup,Stefan Preitl,Emil M. Petriu,Raul-Cristian Roman,Claudia-Adina Bojan-Dragos,Elena-Lorena Hedrea,Alexandra-Iulia Szedlak-Stinean +6 more
TL;DR: A stability analysis approach based on the application of the center manifold theory and applied to state feedback Takagi-Sugeno-Kang fuzzy control systems for the position control of an electro-hydraulic servo-system is proposed.
Journal ArticleDOI
Extracting Valuable Information from Big Data for Machine Learning Control: An Application for a Gas Lift Process
Ana Carolina Spindola Rangel Dias,Felipo Rojas Soares,Johannes Jäschke,Maurício B. de Souza,José Carlos Pinto +4 more
TL;DR: It was observed that the size and the dynamic content of the training set tightly affected the network performance, but for data sets with reasonable information contents, the obtained ESN performance could be regarded as very good, even when longer prediction horizons were proposed.
Journal ArticleDOI
Black-box Modeling for Aircraft Maneuver Control with Bayesian Optimization
TL;DR: The proposed controller can be an alternative to PID control, particularly when both controller structure and controlled plant model information are unknown, and shows shorter flight times and smaller deviations navigating fixed waypoints compared to the tuned Proportional Integral Derivatives (PID) controller.
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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