Book ChapterDOI
System Identification I
Biao Huang,Yutong Qi,Akm Monjur Murshed +2 more
- pp 31-56
About:
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
Citations
More filters
Journal ArticleDOI
A comprehensive review of digital twin — part 1: modeling and twinning enabling technologies
Adam Thelen,Xiaoye Zhang,Olga Fink,Yan Lu,Sayan Ghosh,Byeng D. Youn,Michael D. Todd,Sankaran Mahadevan,Chao Hu,Zhenxiu Hu +9 more
TL;DR: In this paper , the fundamental role of different modeling techniques, twinning enabling technologies, and uncertainty quantification and optimization methods commonly used in digital twins are examined, and a battery digital twin is demonstrated, and more perspectives on the future of digital twin are shared.
Proceedings ArticleDOI
System identification of essential oil extraction system using Non-Linear Autoregressive Model with Exogenous Inputs (NARX)
Farahida Awadz,Ihsan Mohd Yassin,Mohd Hezri Fazalul Rahiman,Mohd Nasir Taib,Azlee Zabidi,Hasliza Hassan +5 more
TL;DR: This paper explores the application of Non-Linear Autoregressive Model with Exogeneous Inputs (NARX) system identification of an essential oil extraction system and defined the 2nd order model with three terms, while fulfilling all model validation criterions.
Journal ArticleDOI
Time Optimal Routing of Electric Vehicles Under Consideration of Available Charging Infrastructure and a Detailed Consumption Model
TL;DR: This study proposes a two-staged approach to compute time optimal routes for EVs using a reduced road network obtained from a leading routing service and a detailed consumption model is applied and the resulting multiobjective shortest path problem is solved using an adapted Moore-Bellman-Ford algorithm.
Journal ArticleDOI
Data-driven fault estimation of non-minimum phase LTI systems
Chengpu Yu,Michel Verhaegen +1 more
TL;DR: This paper studies the data-driven fault estimation for non-minimum phase (NMP) systems and the proposed fault estimator is the sum of a stable causal filter and a stable anti-causal filter, which is shown to be asymptotically unbiased and its performance is demonstrated by numerical simulations.
Proceedings ArticleDOI
Exploiting self-similarity for change detection
Giacomo Boracchi,Manuel Roveri +1 more
TL;DR: A novel change-detection test to detect structural changes in time series by analyzing their self-similarity, which is obtained by comparing each patch to be analyzed with its most similar counterpart in a change-free training set.
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.
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.