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System Identification I

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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.

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Journal ArticleDOI

Conditions for Identifiability Using Routine Operating Data for a First-Order ARX Process Regulated by a Lead-Lag Controller

TL;DR: In this paper, the closed-loop identifiability conditions for a first-order autoregressive process with exogenous input (ARX) that is regulated using a 3-parameter lead-lag controller and that has no external excitation was examined using an analytical approach.
Proceedings ArticleDOI

Robust tube-based predictive control of blood glucose concentration in type 1 diabetes

TL;DR: Results on a virtual subject show that robustness to uncertainties can be improved and the risk of hypoglycemia reduced, without increasing the online computational demands compared to the conventional model predictive control approach.
Proceedings ArticleDOI

Direct identification of continuous-time LPV models

TL;DR: To provide consistent model parameter estimates in this setting, a refined instrumental variable approach is proposed and the statistical properties of this approach are demonstrated through a Monte Carlo simulation example.
Proceedings ArticleDOI

Context is Everything: Implicit Identification for Dynamics Adaptation

TL;DR: Implicit Identification for Dynamics Adaptation (IIDA), a simple method to allow predictive models to adapt to changing environment dynamics, is proposed and demonstrated's ability to perform well in unseen environments is demonstrated.
Posted ContentDOI

Revealing complex ecological dynamics via symbolic regression

TL;DR: This work finds that as the size of the ecosystem increases or the complexity of the inter-species interactions grow, using a dictionary of known functional responses opens the door to correctly reverse-engineer large ecosystems.
References
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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.
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

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

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.