Book ChapterDOI
System Identification I
Biao Huang,Yutong Qi,Akm Monjur Murshed +2 more
- pp 31-56
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The article was published on 2012-12-11. It has received 1704 citations till now. The article focuses on the topics: Nonlinear system identification & System identification.read more
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Proceedings ArticleDOI
Design of excitation signals for nonparametric measurements on MIMO-systems in the presence of nonlinear distortions
TL;DR: It is shown that, using well designed periodic excitations signals, it is possible to obtain nonparametric measurements on a system with two inputs and two outputs with little user interaction, making the method accessible for non-experienced users.
Dynamic Model Formulation and Calibration for Wheeled Mobile Robots
TL;DR: This thesis presents novel WMR model formulations that are high-fidelity, general, modular, and fast, and presents a novel Integrated Prediction Error Minimization (IPEM) method to calibrate model parameters that is general, convenient, online, and evaluative.
Journal ArticleDOI
Temperature Model Identification of FTU Liquid Lithium Limiter
M.L. Apicella,Arturo Buscarino,Claudia Corradino,Luigi Fortuna,G. Mazzitelli,Maria Gabriella Xibilia +5 more
TL;DR: The model identification of the temperature over the surface of the limiter adopted in the Frascati Tokamak Upgrade (FTU) is presented and a comparison among the two models will be given, showing also which physical quantities are relevant to the specific modeling problem.
Journal ArticleDOI
On recursive parametric identification of wiener systems
TL;DR: It is shown here that the problem of parametric identification of a Wiener system could be reduced to a linear parametric estimation problem by a simple input-output data reordering and by a following data partition.
Journal ArticleDOI
Data Consistency Approach to Model Validation
TL;DR: A general criterion to evaluate the consistency of a set of statistical models with respect to observed data is proposed by automatically gauging the models’ ability to generate data that is similar to the observed data.
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.
Journal ArticleDOI
Deep learning in neural networks
TL;DR: This historical survey compactly summarizes relevant work, much of it from the previous millennium, review deep supervised learning, unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks.
Journal ArticleDOI
Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control
Milan Korda,Igor Mezic +1 more
TL;DR: This work extends the Koopman operator to controlled dynamical systems and applies the Extended Dynamic Mode Decomposition (EDMD) to compute a finite-dimensional approximation of the operator in such a way that this approximation has the form of a linearcontrolled dynamical system.
Journal ArticleDOI
A Tour of Reinforcement Learning: The View from Continuous Control
TL;DR: The authors surveys reinforcement learning from the perspective of optimization and control, with a focus on continuous control applications, and reviews the general formulation, terminology, and techniques for reinforcement learning for continuous control.
Journal ArticleDOI
SPICE: A Sparse Covariance-Based Estimation Method for Array Processing
Petre Stoica,Prabhu Babu,Jian Li +2 more
TL;DR: This paper presents a novel SParse Iterative Covariance-based Estimation approach, abbreviated as SPICE, to array processing, obtained by the minimization of a covariance matrix fitting criterion and is particularly useful in many- snapshot cases but can be used even in single-snapshot situations.