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Journal ArticleDOI

From model-based control to data-driven control: Survey, classification and perspective

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.
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This article is published in Information Sciences.The article was published on 2013-06-01. It has received 828 citations till now.

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Citations
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Proceedings ArticleDOI

A Modified VRFT Approach for Retuning Power System Damping Controllers

TL;DR: In this paper, a data-driven method for adjusting power system damping controllers is presented, based on the adaptation of the Virtual Reference Feedback Tuning procedure for the retuning of a selected power system stabilizer.

Payload analysis and control of manipulators for human interactive environments

TL;DR: This doctoral thesis presents the results of numerical simulations and some experimental analysis of the dynamical modeling of multiple degree of freedom (MDoF) manipulators, and proposed and evaluated a methodology for DLCC computation in the entire workspace of manipulators for different types of controllers.
Proceedings ArticleDOI

Data-driven semi-global discrete-time nonlinear output tracking

TL;DR: In this article, a data-driven output tracking controller design method is proposed under the assumption the model of the plant is unavailable, where the controller is designed directly from data, and complexity in building the model and modeling error are avoided.
Proceedings ArticleDOI

Interval Regression Modeling by Linear Programming Support Vector Learning Approach and L∞-Norm

TL;DR: In this paper , an interval regression model for uncertain nonlinear systems is proposed, which combines sparsity stemming from the idea of linear programming support vector learning approach, and modeling accuracy guaranteed by measuring the minimization of maximum regarding the selection of approximation error between the actual output and the estimated out.
Proceedings ArticleDOI

Data-Driven Control for Self-Balancing Two-Wheeled Scooter

TL;DR: In this article , a self-balancing two-wheeled scooter is a nonlinear and unstable system and its stabilization is an interesting problem and many methods have been developed for stabilizing this system.
References
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Book

System Identification: Theory for the User

Lennart Ljung
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

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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