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
Data-Driven Model-Free Adaptive Predictive Control for a Class of MIMO Nonlinear Discrete-Time Systems With Stability Analysis
TL;DR: A model-free adaptive predictive control method is proposed for a class of unknown nonlinear non-affine multiple-input and multiple-output (MIMO) systems based on a novel dynamic linearization technique and a new time-varying Pseudo–Jacobian matrix (PJM) parameter.
Posted Content
Low-complexity Learning of Linear Quadratic Regulators from Noisy Data
Claudio De Persis,Pietro Tesi +1 more
TL;DR: This paper considers the Linear Quadratic Regulator problem for linear systems with unknown dynamics, a central problem in data-driven control and reinforcement learning, and proposes a method that uses data to directly return a controller without estimating a model of the system.
Journal ArticleDOI
Local learning-based model-free adaptive predictive control for adjustment of oxygen concentration in syngas manufacturing industry
TL;DR: In this paper, a data-driven control method called compact-form-dynamic-linearisation-based model-free adaptive predictive control approach combined with the local learning (LL-CFDL-MFAPC) is proposed to address the control problem.
Journal ArticleDOI
Data-Driven Methods for Stealthy Attacks on TCP/IP-Based Networked Control Systems Equipped With Attack Detectors
Jun-Sheng Wang,Guang-Hong Yang +1 more
TL;DR: This paper aims to remove the aforementioned conservative assumptions and give a stealthy attack methodology for closed-loop CPS with reference signals, that is, transmission control protocol/Internet protocol (TCP/IP)-based networked control systems.
Journal ArticleDOI
Data-driven adaptive fractional order PI control for PMSM servo system with measurement noise and data dropouts.
TL;DR: In this paper, data-driven adaptive fractional order proportional integral (AFOPI) control is presented for permanent magnet synchronous motor (PMSM) servo system perturbed by measurement noise and data dropouts.
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.
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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.
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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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