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
More filters
Book ChapterDOI
Time Inconsistency and Self-Control Optimization Problems: Progress and Challenges
Yun Shi,Xiangyu Cui +1 more
TL;DR: Different approaches dealing with time inconsistency in the literature are reviewed and the open questions and challenges are also discussed.
Posted Content
Automatic Policy Synthesis to Improve the Safety of Nonlinear Dynamical Systems
TL;DR: A two-player collaborative algorithm is proposed that alternates between estimating a Lyapunov function and deriving a controller that gradually enlarges the stability region of the closed-loop system to obtain control policies with large safe regions.
Journal ArticleDOI
Local linear regression for efficient data-driven control
TL;DR: The aim of this work is the study of an efficient DDC approach for nonlinear dynamic systems that exploits the data directly coming from the plant by using local linear regression models chosen for their simplicity of training and efficiency in incorporating new data generated by the plant.
Proceedings ArticleDOI
Data-Driven Positive Stabilization of Linear Systems
TL;DR: This paper provides an initial attempt to solve the positive stabilization of linear systems by input-output data using data-dependent linear matrix inequalities and finds that no subspace identification is required to obtain system matrices.
Journal ArticleDOI
Data-Driven Optimal Control of Linear Time-Invariant Systems
TL;DR: This paper proposes an open-loop optimal feedback control scheme and shows that its efficient implementation requires solution of a number of optimal estimation problems and a deterministic optimal control problem, all in data-driven formulations.
References
More filters
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.
Related Papers (5)
A Novel Data-Driven Control Approach for a Class of Discrete-Time Nonlinear Systems
Zhongsheng Hou,Shangtai Jin +1 more
Data-Driven Model-Free Adaptive Control for a Class of MIMO Nonlinear Discrete-Time Systems
Zhongsheng Hou,Shangtai Jin +1 more