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Probabilistic energy forecasting using quantile regressions based on a new nearest neighbors quantile filter

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arXiv 2019年

作者： Ordiano, Jorge Ángel González Gröll, Lutz Mikut, Ralf Hagenmeyer, Veit Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Hermann-von-Helmholtz-Platz 1 Eggenstein-Leopoldshafen76344 Germany

Parametric quantile regressions are a useful tool for creating probabilistic energy forecasts. Nonetheless, since classical quantile regressions are trained using a non-differentiable cost function, their creation using complex data mining techniques (e.g., artificial neural networks) may be complicated. This article presents a method that uses a new nearest neighbors quantile filter to obtain quantile regressions independently of the utilized data mining technique and without the non-differentiable cost function. Thereafter, a validation of the presented method using the dataset of the Global Energy Forecasting Competition of 2014 is undertaken. The results show that the presented method is able to solve the competition's task with a similar accuracy and in a similar time as the competition's winner, but requiring a much less powerful computer. This property may be relevant in an online forecasting service for which the fast computation of probabilistic forecasts using not so powerful machines is required. Copyright © 2019, The Authors. All rights reserved.

关键词： Forecasting

OptoShield: A Low-Cost Tool for Control and Mechatronics Education

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OptoShield: A Low-Cost Tool for Control and Mechatronics Edu...

Asian Control Conference

作者： Gergely Takács Tibor Konkoly Martin Gulan Institute of Automation Measurement and Applied Informatics Faculty of Mechanical Engineering Slovak University of Technology in Bratislava Bratislava Slovakia

ISBN: (纸本)9781728102634

Commercial educational tools for teaching feedback concepts in control systems engineering and mechatronics are generally expensive, large, complex and sensitive instruments; therefore cannot be used for homework assignments outside the classroom. This paper presents a novel open-source teaching aid that can be readily manufactured under AC3 and as such, is financially accessible to students and universities operating on a tight budget. The device proposed in this paper implements a simple optical experiment, allowing students to follow a prescribed brightness level using feedback control concepts. In addition to real-time control, the apparatus is also suitable for teaching signal processing and system identification principles. The educational aid presented here is attached to the popular Arduino microcontroller prototyping platform in a form of a miniature extension shield, thereby using a standardized physical layout and software ecosystem. We describe the hardware, the application programming interface (API) and library written in C/C++ for the Arduino integrated development environment (IDE) and the accompanying Simulink toolbox; moreover present sample exercises for system identification and proportional-integral-derivative (PID) control.

关键词： Light emitting diodes Hardware Education Software packages Resistors Open source software

Real-time Stabilizing MPC of a 2DOF Helicopter

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Real-time Stabilizing MPC of a 2DOF Helicopter

International Conference on Process Control (PC)

作者： Martin Gulan Peter Minarčík Martin Lizúch Institute of Automation Measurement and Applied Informatics Faculty of Mechanical Engineering Slovak University of Technology in Bratislava Bratislava Slovakia

This paper presents real-time control of a laboratory helicopter model with two degrees of freedom. To accomplish this goal we propose to employ a numerically robust approach to the synthesis of stabilizing model predictive control based on model prestabilization before the prediction phase. The underlying optimal control algorithm involves integral action, input constraints imposed by actuators, and guarantees closed-loop stability and recursive feasibility via a low-complexity terminal set constraint. Performance of the controller is practically demonstrated in the task of tracking a state reference corresponding to a predefined flight trajectory, and compared with linear quadratic control.

关键词： Helicopters Numerical models Predictive models Mathematical model Rotors Computational modeling Propellers

Energy-efficient Swing-up and MPC Stabilization of an Inverted Pendulum

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Energy-efficient Swing-up and MPC Stabilization of an Invert...

International Conference on Process Control (PC)

作者： Martin Gulan Peter Minarčík Jakub Kulhánek Institute of Automation Measurement and Applied Informatics Faculty of Mechanical Engineering Slovak University of Technology in Bratislava Bratislava Slovakia

This article presents a control framework to swing up and stabilize the inverted pendulum-cart system in its unstable equilibrium and maintain this configuration while changing the reference position of the cart. The swing-up problem is solved by an energy-based approach that respects physical constraints of the system. Stabilization and subsequent cart position tracking is addressed by means of an implicit model predictive controller with guaranteed stability imposed via a terminal set constraint. Viability of the proposed framework is practically demonstrated on a laboratory inverted pendulum system, the states of which were estimated by a continuous-discrete extended Kalman filter.

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Fog Oriented Model for Data Collection in the Networks of Mobile Devices

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Fog Oriented Model for Data Collection in the Networks of Mo...

International IEEE Conference on Intelligent Systems, IS

作者： Alexander Vodyaho Radoslav Yoshinov Nataly Zhukova Aung Myo Thaw Abbas Saddam Ahmed St. Petersburg State Electrotechnical University St. Petersburg Russia Educational Telematics Bulgarian Academy of Sciences Sofia Bulgaria St. Petersburg Institute for Informatics and Automation Russian Academy of Sciences St. Petersburg Russia Department of Informatics and Applied Mathematics ITMO University St. Petersburg Russia

ISBN: (数字)9781728154565

ISBN: (纸本)9781728154572

In the current state of IoT systems development, the fog techniques become the key solution of latency and energy consumption reducing when collecting and processing end user data. Instead of processing and storing data in the cloud, the fog technique extends the responsibility of cloud nearer to the end user and it allows improve QoS and decrease communication cost. In this paper a fog-oriented data collection model which uses processing functions in the fog layer is presented. Moreover, the responsibilities of cloud service and fog data processing are defined for deferent smart application.

关键词： Data collection Data models Computational modeling Security Middleware Mobile handsets

Towards automatic embryo staging in 3d+t microscopy images using convolutional neural networks and pointnets

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arXiv 2019年

作者： Traub, Manuel Stegmaier, Johannes Institute of Imaging and Computer Vision RWTH Aachen University Aachen Germany Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany

Automatic analyses and comparisons of different stages of embryonic development largely depend on a highly accurate spatio-temporal alignment of the investigated data sets. In this contribution, we compare multiple approaches to perform automatic staging of developing embryos that were imaged with time-resolved 3D light-sheet microscopy. The methods comprise image-based convolutional neural networks as well as an approach based on the PointNet architecture that directly operates on 3D point clouds of detected cell nuclei centroids. The proof-of-concept experiments with four wild-type zebrafish embryos render both approaches suitable for automatic staging with average deviations of 0.45 − 0.57 hours. Copyright © 2019, The Authors. All rights reserved.

关键词： Biology

MPC-DICE: An open-source Matlab implementation of receding horizon solutions to DICE

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IFAC-PapersOnLine 2018年第5期51卷 120-125页

作者： Faulwasser, Timm Kellett, Christopher M. Weller, Steven R. Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen76344 Germany School of Electrical Engineering and Computing University of Newcastle CallaghanNew South Wales2308 Australia

The most widely used integrated assessment model for studying the economics of climate change is the Dynamic Integrated model of Climate and Economy (DICE). DICE is a nonlinear, time-varying discrete-time system whereby important quantities are calculated by solving an associated optimal control problem. Here, we describe an open-source Matlab implementation of the DICE model which uses Model Predictive Control (MPC) to approximately solve the DICE optimal control problem. © 2018

关键词： Climate change

Asymptotic stabilization of a system of coupled nth–order differential equations with potentially unbounded high-frequency oscillating perturbations

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arXiv 2019年

作者： Vrabel, R. Slovak University of Technology in Bratislava Institute of Applied Informatics Automation and Mechatronics Bottova 25 Trnava917 01 Slovakia

This paper deals with an analysis and design of robust, state-feedback control law uniform-asymptotically stabilizing at origin the system consisting of coupled nth–order ordinary differential equations in the presence of a non-vanishing at x = 0 or even unbounded on the time interval [0, ∞) time-varying high-frequency oscillating perturbation w(t, x). The obtained results generalize and extend some known and now classical results in the control theory for a wider class of perturbations. Moreover, as is shown in the paper, there is no room for further generalization for w which is time-dependent only, w = w(t).MSC Codes 93C10 93D15 93D20 Copyright © 2019, The Authors. All rights reserved.

关键词： State feedback

Lockdown effects on air quality in megacities during the first and second waves of COVID-19 pandemic

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arXiv 2020年

作者： Giri, Aswin J. Schäfer, Benjamin Verma, Rulan He, Hankun Nagendra, S.M. Shiva Khare, Mukesh Beck, Christian Indian Institute of Technology Madras India Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen76344 Germany School of Mathematical Sciences Queen Mary University of London United Kingdom Indian Institute of Technology Delhi India The Alan Turing Institute 96 Euston Road LondonNW1 2DB United Kingdom

Air pollution is among the highest contributors to mortality worldwide, especially in urban areas. During spring 2020, many countries enacted social distancing measures in order to slow down the ongoing COVID-19 pandemic. A particularly drastic measure, the "lockdown", urged people to stay at home and thereby prevent new COVID-19 infections during the first (2020) and second wave (2021) of the pandemic. In turn, it also reduced traffic and industrial activities. But how much did these lockdown measures improve air quality in large cities, and are there differences in how air quality was affected? Here, we analyse data from two megacities: London as an example for Europe and Delhi as an example for Asia. We consider data during first and second wave lockdowns and compare them to 2019 values. Overall, we find a reduction in almost all air pollutants with intriguing differences between the two cities except Delhi in 2021. In London, despite smaller average concentrations, we still observe high-pollutant states and an increased tendency towards extreme events (a higher kurtosis of the probability density during lockdown) during 2020 and low pollution levels during 2021. For Delhi, we observe a much stronger decrease of pollution concentrations, including high pollution states during 2020 and higher pollution levels in 2021. These results could help to design policies to improve long-term air quality in megacities. Copyright © 2020, The Authors. All rights reserved.

关键词： Air quality