scispace - formally typeset
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.
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
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

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

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
More filters
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.
Related Papers (5)