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
Enhanced sensitivity shaping by data-based tuning of disturbance observer with non-binomial filter.
TL;DR: This work presents a new method of sensitivity shaping for motion control systems with disturbance observer (DOB) that is data-based in the sense that the sensitivity shaping process is conducted based on the input-output data collected from the operating motion system, instead of relying on the identified system model.
Journal ArticleDOI
Balancing and Reconstruction of Segmented Postures for Humanoid Robots in Imitation of Motion
Jin-Ling Lin,Kao-Shing Hwang +1 more
TL;DR: The experimental results demonstrate that a robot could adjust the poses, mapped from the movements of the demonstrator, to its static stable states, thereby imitating human motions by self-learning.
Journal ArticleDOI
Sampling Strategies for Data-Driven Inference of Input–Output System Properties
TL;DR: These sampling strategies are based on gradient dynamical systems and saddle point flows to solve the reformulated optimization problems, where the gradients can be evaluated from only input–output data samples, and their convergence properties are discussed in continuous time and discrete time.
Journal ArticleDOI
Data-based predictive control for networked non-linear multi-agent systems consensus tracking via cloud computing
Haoran Tan,Zhiwu Huang,Min Wu +2 more
TL;DR: This study investigates the consensus tracking problem for a class of networked non-linear multi-agent systems (NNMASs) using cloud computing and proposes a data-based cloud predictive control scheme, which only depends on the historical input and output data of the agents without using the explicit or implicit information of its structure.
Journal ArticleDOI
Knowledge-based reinforcement learning controller with fuzzy-rule network: experimental validation
TL;DR: A model-free controller for a general class of output feedback nonlinear discrete-time systems is established by action-critic networks and reinforcement learning with human knowledge based on IF–THEN rules.
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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