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PoCET: a Polynomial Chaos Expansion Toolbox for Matlab

IFAC-PapersOnLine 2020年第2期53卷 7256-7261页

作者： Felix Petzke Ali Mesbah Stefan Streif Automatic Control & System Dynamics Lab at Technische Universität Chemnitz Faculty for Electrical Engineering and Information Technology Chemnitz Germany Department of Chemical and Biomolecular Engineering University of California Berkeley CA USA

We introduce PoCET: a free and open-scource Polynomial Chaos Expansion Toolbox for Matlab, featuring the automatic generation of polynomial chaos expansion (PCE) for linear and nonlinear dynamic systems with time-invariant stochastic parameters or initial conditions, as well as several simulation tools. It offers a built-in handling of Gaussian, uniform, and beta probability density functions, projection and collocation-based calculation of PCE coefficients, and the calculation of stochastic moments from a PCE. Efficient algorithms for the calculation of the involved integrals have been designed in order to increase its applicability. PoCET comes with a variety of introductory and instructive examples. Throughout the paper we show how to perform a polynomial chaos expansion on a simple ordinary differential equation using PoCET, as well as how it can be used to solve the more complex task of optimal experimental design.

关键词： polynomial chaos simulation tools optimal experiment design optimal control

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Automation Software Architecture in CPPS - Definition, Challenges and Research Potentials

Automation Software Architecture in CPPS - Definition, Chall...

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Industrial Cyber-Physical systems (ICPS)

作者： Birgit Vogel– Heuser Eva– Maria Neumann Juliane Fischer Marga Marcos Elisabet Esté vez Esté vez Giacomo Barbieri Lisa Sonnleithner Rick Rabiser Institute of Automation and Information Systems TUM School of Engineering and Design Core Member of MDSI Member of MIRMI Technical University of Munich Garching Germany Institute of Automation and Information Systems TUM School of Engineering and Design Technical University of Munich Garching Germany Department of Automatic Control and System Engineering ETSI Bilbao Basque Country University Bilbao Spain Electronics and Automation Engineering Department University of Ja&#x00E9 n Ja&#x00E9 n Spain Department of Mechanical Engineering Universidad de los Andes Bogot&#x00E1 Colombia CDL VaSiCS LIT CPS Lab Johannes Kepler University Linz Linz Austria

The importance of a mature, maintainable design of automation software in Cyber-Physical Production systems (CPPS) is continuously increasing since a growing proportion of the system functionality is implemented via software. As a result, system complexity is shifting more and more towards the software side. Quality characteristics such as flexibility, maintainability, and extensibility, whose importance is increasing in the context of Industry 4.0, are thus becoming harder to achieve. These challenges can only be solved through sound architectural design. While there is a common understanding of good software architecture and appropriate methods to achieve it in computer science, a suitable architecture definition for automation software that takes all relevant factors into account is still missing in the field of CPPS. Therefore, based on a workshop with international scientists with different perspectives on CPPS, this paper presents influencing factors on automation software architecture. On this basis, a joint definition for software architecture in CPPS, as well as challenges and future research potentials, are derived.

关键词： Computer science Production systems Software architecture Conferences Computer architecture Cyber-physical systems Software

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A Data Driven Condition Monitoring of Chain Type Structures by Using Nonlinear Frequency Analyses 2

A Data Driven Condition Monitoring of Chain Type Structures ...

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2nd International Conference on Industrial Artificial Intelligence, IAI 2020

作者： Gao, Yi Luo, Zhong Zhu, Yunpeng Qiu, Yue Li, Yuqi Key Laboratory of Vibration and Control of Aero-Propulsion Systems Ministry of Education of China Northeastern University Shenyang110819 China State Key Laboratory of Structural Analysis for Industrial Equipment Dalian University of Technology Dalian116024 China University of Sheffield Department of Automatic Control and System Engineering SheffieldS13JD United Kingdom

ISBN: (纸本)9781728182162

A novel data driven condition monitoring approach is proposed in this study to detect the location of nonlinear faults in chain type structures. In this approach, the chain type system is characterized by representing the relationships between any two adjacent measurement points by NARX (Nonlinear Auto-Regressive with Exogenous Inputs) model. A new indicator for condition monitoring, known as the NET (Nonlinear Energy Transmission) indicator, is introduced based on the evaluation of the NRSFs (Nonlinear Response Spectrum Functions) of the chain type system. A 3 DOF system is employed to demonstrate the application of the data driven condition monitoring by using the NET indicator. A case study on the condition monitoring of a rotor-bearing system is then discussed to validate the advantage of the proposed approach in engineering practice. © 2020 IEEE.

关键词： Condition monitoring

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Magnetic Sensor Based Topographic Localization for automatic Dislocation of Ingested Button Battery

Magnetic Sensor Based Topographic Localization for Automatic...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jialun Liu Hironari Sugiyama Tadachika Nakayama Shuhei Miyashita Department of Automatic Control and System Engineering University of Sheffield Sheffield UK Department of Science of Technology Innovation Nagaoka University of Technology Nagaoka Niigata Japan

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

A button battery accidentally ingested by a toddler or small child can cause severe damage to the stomach within a short period of time. Once a battery lands on the surface of the esophagus or stomach, it can run a current in the tissue and induce a chemical reaction resulting in injury. Following our previous work where we presented an ingestible magnetic robot for button battery retrieval, this study presents a remotely achieved novel localization method of a button battery with commonly available magnetic sensors (Hall-effect sensors). By applying a direct magnetic field to the button battery using an electromagnetic coil, the battery is magnetized, and hence it becomes able to be sensed by Hall-effect sensors. Using a trilateration method, we were able to detect the locations of an LR44 button battery and other ferromagnetic materials at variable distances. Additional four electromagnetic coils were used to autonomously navigate a magnet-containing capsule to dislocate the battery from the affected site.

关键词： Batteries Magnetic sensors Magnetic resonance imaging Magnetization Magnetic separation Stomach

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Weighted Transfer Learning of Dynamic Time Warped Data for Motor Imagery based Brain Computer Interfaces

Weighted Transfer Learning of Dynamic Time Warped Data for M...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Joshua Giles Kai Keng Ang Lyudmila Mihaylova Mahnaz Arvaneh Automatic control and System Engineering Department University of Sheffield Sheffield UK Institute for Infocomm Research Agency for Science Technology and Research (A*STAR) Singapore

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

A large amount of calibration data is typically needed to train an electroencephalogram (EEG)-based brain-computer interfaces (BCI) due to the non-stationary nature of EEG data. This paper proposes a novel weighted transfer learning algorithm using a dynamic time warping (DTW) based alignment method to alleviate this need by using data from other subjects. DTW-based alignment is first applied to reduce the temporal variations between a specific subject data and the transfer learning data from other subjects. Next, similarity is measured using Kullback Leibler divergence (KL) between the DTW aligned data and the specific subject data. The other subjects' data are then weighted based on their KL similarity to each trials of the specific subject data. This weighted data from other subjects are then used to train the BCI model of the specific subject. An experiment was performed on publicly available BCI Competition IV dataset 2a. The proposed algorithm yielded an average improvement of 9% compared to a subject-specific BCI model trained with 4 trials, and the results yielded an average improvement of 10% compared to naive transfer learning. Overall, the proposed DTW-aligned KL weighted transfer learning algorithm show promise to alleviate the need of large amount of calibration data by using only a short calibration data.

关键词： Calibration Electroencephalography Heuristic algorithms Brain modeling Data models Training Feature extraction

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Constrained extremum seeking: A modified-barrier function approach 11

Constrained extremum seeking: A modified-barrier function ap...

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11th IFAC Symposium on Nonlinear control systems, NOLCOS 2019

作者： Labar, Christophe Garone, Emanuele Kinnaert, Michel Ebenbauer, Christian Department of Control Engineering and System Analysis Université libre de Bruxelles Brussels1050 Belgium Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart70569 Germany

In this paper, we address the problem of steering the input of a convex function to a value that minimizes the function under a convex constraint. We consider the case where the constraint cannot be violated of more than a user-defined value during the whole transient phase. The mathematical expression of both the cost function and the constraint are assumed to be unknown. The only information available are the on-line values of the cost and the constraint. To tackle this problem, an optimization law, based on a modified-barrier function, and involving the gradient of both the cost function and the constraint, is firstly designed. The Lie bracket formalism is then exploited to approximate this law, by combining time-periodic signals with the on-line measurements of both the cost and the constraint. The stability property of the resulting constrained extremum seeking system is proved, and its effectiveness is shown in simulation. © 2019, IFAC (International Federation of automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Cost functions

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Tutorial on Asymptotic Properties of Regularized Least Squares Estimator for Finite Impulse Response Model

arXiv

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arXiv 2021年

作者： Ju, Yue Chen, Tianshi Mu, Biqiang Ljung, Lennart The School of Data Science Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen518172 China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and System Science Chinese Academy of Sciences Beijing100190 China The Division of Automatic Control Department of Electrical Engineering Linköping University LinköpingSE-58183 Sweden

In this paper, we give a tutorial on asymptotic properties of the Least Square (LS) and Regularized Least Squares (RLS) estimators for the finite impulse response model with filtered white noise inputs. We provide three perspectives: the almost sure convergence, the convergence in distribution and the boundedness in probability. On one hand, these properties deepen our understanding of the LS and RLS estimators. On the other hand, we can use them as tools to investigate asymptotic properties of other estimators, such as various hyper-parameter estimators. © 2021, CC BY.

关键词： Probability distributions

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PoCET: a Polynomial Chaos Expansion Toolbox for Matlab

arXiv

引用

arXiv 2020年

作者： Petzke, Felix Mesbah, Ali Streif, Stefan Automatic Control & System Dynamics Lab Technische Universität Chemnitz Faculty for Electrical Engineering and Information Technology Chemnitz Germany Department of Chemical and Biomolecular Engineering University of California BerkeleyCA United States

关键词： Nonlinear dynamical systems

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Cross-subjects Emotions Classification from EEG Signals using a Hierarchical LSTM based Classifier

Cross-subjects Emotions Classification from EEG Signals usin...

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E-Health and Bioengineering Conference (EHB)

作者： Bogdan Badicu Andreea Udrea Department of Automatic Control and System Engineering University Politehnica Bucharest Bucharest Romania

This article focuses on cross subjects' emotions classification from electroencephalogram signals (EEG). We propose a hierarchical classifier based on Long Short Term Memory (LSTM) neural networks for this task. For model training and testing, we use the signals from SEED database. Cross subjects emotions classification into neutral, positive and negative achieved an accuracy of 80% when using the proposed method.

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Structural recurrent neural network for traffic speed prediction

arXiv

引用

arXiv 2019年

作者： Kim, Youngjoo Wang, Peng Mihaylova, Lyudmila University of Sheffield Department of Automatic Control and System Engineering Sheffield United Kingdom

Deep neural networks have recently demonstrated the traffic prediction capability with the time series data obtained by sensors mounted on road segments. However, capturing spatio-temporal features of the traffic data often requires a significant number of parameters to train, increasing computational burden. In this work we demonstrate that embedding topological information of the road network improves the process of learning traffic features. We use a graph of a vehicular road network with recurrent neural networks (RNNs) to infer the interaction between adjacent road segments as well as the temporal dynamics. The topology of the road network is converted into a spatio-temporal graph to form a structural RNN (SRNN). The proposed approach is validated over traffic speed data from the road network of the city of Santander in Spain. The experiment shows that the graphbased method outperforms the state-of-the-art methods based on spatio-temporal images, requiring much fewer parameters to train. Copyright © 2019, The Authors. All rights reserved.

关键词： Recurrent neural networks

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