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Influence of Time-Delay Mismatch for Robustness and Stability

IFAC-PapersOnLine 2018年第14期51卷 248-253页

作者： Bányász, Cs. Keviczky, L. Bars, R. Institute of Computer Science and Control Hungarian Academy of Sciences H-1111 Budapest Kendeu 13-17 Hungary Department of Automation and Applied Informatics Budapest University of Technology and Economics H-1117 Budapest Magyar Tudósok krt 2 Q/B Hungary

In a practical control system the process always has a time delay. The uncertainty in the knowledge of the time delay i.e. the delay mismatch strongly influences the quality of the closed-loop control. It can cause unwanted instability and influences the robustness of the control. Stability region applicable for this uncertainty is investigated in this paper in connection with the required performance and robustness. © 2018

关键词： Delay control systems Convergence of numerical methods Quality control Robust control Robustness (control systems) Stability Time delay Timing circuits Closed loop control Delay mismatch performance Practical controls Stability regions Time delay uncertainties

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Two-timescale voltage control in distribution grids using deep reinforcement learning

arXiv

引用

arXiv 2019年

作者： Yang, Qiuling Wang, Gang Sadeghi, Alireza Giannakis, Georgios B. Sun, Jian State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States

Modern distribution grids are currently being challenged by frequent and sizable voltage fluctuations, due mainly to the increasing deployment of electric vehicles and renewable generators. Existing approaches to maintaining bus voltage magnitudes within the desired region can cope with either traditional utility-owned devices (e.g., shunt capacitors), or contemporary smart inverters that come with distributed generation units (e.g., photovoltaic plants). The discrete on-off commitment of capacitor units is often configured on an hourly or daily basis, yet smart inverters can be controlled within milliseconds, thus challenging joint control of these two types of assets. In this context, a novel two-timescale voltage regulation scheme is developed for distribution grids by judiciously coupling data-driven with physicsbased optimization. On a faster timescale, say every second, the optimal setpoints of smart inverters are obtained by minimizing instantaneous bus voltage deviations from their nominal values, based on either the exact alternating current power flow model or a linear approximant of it;whereas, on the slower timescale (e.g., every hour), shunt capacitors are configured to minimize the longterm discounted voltage deviations using a deep reinforcement learning algorithm. Extensive numerical tests on a real-world 47-bus distribution network as well as the IEEE 123-bus test feeder using real data corroborate the effectiveness of the novel scheme. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep learning

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A statistical learning approach to reactive power control in distribution systems

arXiv

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arXiv 2019年

作者： Yang, Qiuling Sadeghi, Alireza Wang, Gang Giannakis, Georgios B. Sun, Jian State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States

Pronounced variability due to the growth of renewable energy sources, flexible loads, and distributed generation is challenging residential distribution systems. This context, motivates well fast, efficient, and robust reactive power control. Real-time optimal reactive power control is possible in theory by solving a non-convex optimization problem based on the exact model of distribution flow. However, lack of high-precision instrumentation and reliable communications, as well as the heavy computational burden of non-convex optimization solvers render computing and implementing the optimal control challenging in practice. Taking a statistical learning viewpoint, the input-output relationship between each grid state and the corresponding optimal reactive power control is parameterized in the present work by a deep neural network, whose unknown weights are learned offline by minimizing the power loss over a number of historical and simulated training pairs. In the inference phase, one just feeds the real-time state vector into the learned neural network to obtain the 'optimal' reactive power control with only several matrix-vector multiplications. The merits of this novel statistical learning approach are computational efficiency as well as robustness to random input perturbations. Numerical tests on a 47-bus distribution network using real data corroborate these practical merits. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

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Statistical Approach to Detection of Attacks for Stochastic Cyber-Physical Systems

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IFAC-PapersOnLine 2018年第25期51卷 178-183页

作者： Marelli, Damián Sui, Tianju Fu, Minyue School of Automation Guandong University of Technology China French-Argentinean International Center for Information and Systems Sciences National Scientific and Technical Research Council Argentina Department of Control Science and Engineering Dalian University of Technology China School of Electrical Engineering and Computer Science University of Newcastle Australia

We study the problem of detecting an attack on a stochastic cyber-physical system. We start by proposing a detection criterion based on checking the statistics of the Kalman prediction error. To show the importance of the proposed criterion, we study certain attacking schemes which can be effectively detected by this criterion, but not by checking simpler conditions based on commonly used statistics. We then use the proposed criterion to derive a detection algorithm. This algorithm is based on a statistical confidence test, giving a confidence level for detecting an attack. We present simulation results to illustrate the performance of this algorithm. © 2018

关键词： computer crime Cyber Physical System Embedded systems Error statistics Linear systems Statistics Stochastic systems Testing Attack detection Detection algorithm Detection of attacks Integrity attacks Statistical approach Statistical confidence Statistical hypothesis testing System security

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Complex issues in regulator designing

Complex issues in regulator designing

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2018 International Russian automation Conference, RusAutoCon 2018

作者： Zhmud, Vadim A. Hardt, Wolfram Dimitrov, Lubomir V. Roth, Hubert Department of Automation Novosibirsk State Technical University Novosibirsk Russia Department of Computer Science Chemnitz University of Technology Chemnitz Germany Technical University of Sofia Sofia Bulgaria Department of Automatic Control Engineering University of Siegen Siegen Germany

ISBN: (纸本)9781538649381

The problem of control object with the use of feedback loop is extremely relevant, because only this method provides for the accurate control. It happened that the theory of automatic control paid much attention to the methods of regulators design based on mathematical transformations, using a mathematical model of the object. It describes the transformation of an input signal into an output signal inside the object. The methods were imperfect, so one of the following simplification methods was the most frequently used: the mathematical model of the object was simplified, or the calculations were carried out with approximation, for example, the oscillations in the system were studied by the amplitude and phase of the first harmonic only. Therefore, the result of using such regulators in practice did not exactly correspond to the theory provisions. To get mathematical and experimental basis of system developer tool, a solution of the elementary sub-problems was required. Among them there are tasks of the control of an object of the first and second order. Today the situation has changed. There is a means of sufficiently accurate mathematical modeling of the behavior of the system consisting of the loop with an object and a regulator. There are software and mathematical means for regulator calculating by the method of numerical optimization. Now there is sufficient software for calculating the regulators of the object, having a rather complex mathematical model. However, this did not change the situation. A lot of articles are still published, in which it is suggested performing additional fine tuning to achieve the required parameters after calculating the regulator and its technical implementation. Quite a big number of articles is still being published;they consider the methods of the empirical tuning of regulators based on the parameters of the transient process with a given fixed gain coefficient. This situation demonstrates insufficient using of the important th

关键词： Mathematical transformations

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Hand gesture classification with use of convolutional neural networks 32

Hand gesture classification with use of convolutional neural...

引用

32nd Annual European Simulation and Modelling Conference, ESM 2018

作者： Grzejszczak, Tomasz Roth, Robert Moller, Reinhard Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science 16 Akademicka Street Gliwice44-100 Poland Department of Automation/Computer Science Univeristy of Wuppertal Rainer-Guenter-Str. 21 Wuppertal42119 Germany

ISBN: (纸本)9789492859051

The preliminary research on stationary sign language hand gesture recognition with use of convolutional neural networks is presented. Three tests are presented that differ in number of gesture types, that is, by classes amount. The main question is, whether it is possible to use convolutional neural networks and deep learning approach in stationary gesture recognition, when there is small number of training data, what is the influence of similar gestures on classification process and is it necessary to use controlled background. Test results are provided in form of confusion matrices. Finally, the direction of future work and further research is discussed. © 2018 PDF-CONFERENCE. All rights reserved.

关键词： Convolution

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Preface

Advances in Intelligent Systems and Computing

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Advances in Intelligent Systems and Computing 2020年 1241 AISC卷 v-vi页

作者： Vittorini, Pierpaolo Di Mascio, Tania Tarantino, Laura Temperini, Marco Gennari, Rosella De la Prieta, Fernando Department of Life Health and Environmental Sciences University of L’Aquila L’Aquila Italy Department of Information Engineering Computer Science and Mathematics University of L’Aquila L’Aquila Italy Computer Science Faculty Free University of Bozen-Bolzano Bolzano Italy Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy Department of Computer Science and Automation Control University of Salamanca Salamanca Spain

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Parallel Dispatch:A New Paradigm of Electrical Power System Dispatch

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IEEE/CAA Journal of Automatica Sinica 2018年第1期5卷 311-319页

作者： Jun Jason Zhang Fei-Yue Wang Qiang Wang Dazhi Hao Xiaojing Yang David Wenzhong Gao Xiangyang Zhao Yingchen Zhang Department of Electrical and Computer Engineering Ritchie School of Engineering and Computer Science University of Denver Denver 80210 CO USA State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Science (SKL-MCCS CASIA) Beijing 100190 China Research Center of Computational Experiments and Parallel Systems The National University of Defense Technology Changsha 410073 China State Grid Tianjin Electric Power Company Tianjin 300010 China School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China National Renewable Energy Laboratory Golden CO 80401 USA IEEE

Modern power systems are evolving into sociotechnical systems with massive complexity, whose real-time operation and dispatch go beyond human capability. Thus,the need for developing and applying new intelligent power system dispatch tools are of great practical significance. In this paper, we introduce the overall business model of power system dispatch, the top level design approach of an intelligent dispatch system, and the parallel intelligent technology with its dispatch applications. We expect that a new dispatch paradigm,namely the parallel dispatch, can be established by incorporating various intelligent technologies, especially the parallel intelligent technology, to enable secure operation of complex power grids,extend system operators' capabilities, suggest optimal dispatch strategies, and to provide decision-making recommendations according to power system operational goals.

关键词： ACP knowledge automation power dispatch parallel dynamic programming parallel intelligence paralle learning situational awareness

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PID2018 Benchmark Challenge: learning feedforward control

引用

IFAC-PapersOnLine 2018年第4期51卷 663-668页

作者： Zhao, Yang Dehghan, Sina Ates, Abdullah Yuan, Jie Zhou, Fengyu Li, Yan Chen, YangQuan School of Control Science and Engineering Center for Robotics Shandong University JinanShandong250061 China University of California Merced MercedCA95340 United States School of Automation Southeast University Nanjing210096 China Engineering Faculty Computer Engineering Department Inonu University Malatya44280 Turkey

The design and application of learning feedforward controllers (LFFC) for the one-staged refrigeration cycle model described in the PID2018 Benchmark Challenge is presented, and its effectiveness is evaluated. The control system consists of two components: 1) a preset PID component and 2) a learning feedforward component which is a function approximator that is adapted on the basis of the feedback signal. A B-spline network based LFFC and a low-pass filter based LFFC are designed to track the desired outlet temperature of evaporator secondary flux and the superheating degree of refrigerant at evaporator outlet. Encouraging simulation results are included. Qualitative and quantitative comparison results evaluations show that, with little effort, a high-performance control system can be obtained with this approach. Our initial simple attempt of low-pass filter based LFFC and B-spline network based LFFC give J=0.4902 and J=0.6536 relative to the decentralized PID controller, respectively. Besides, the initial attempt of a combination controller of our optimized PI controller and low-pass filter LFFC gives J=0.6947 relative to the multi-variable PID controller. © 2018

关键词： controllers Benchmarking Electric control equipment Evaporators Feedforward control Interpolation Learning systems Low pass filters Proportional control systems Refrigeration Three term control systems Combination controllers Conditional integrations Decentralized PID controller Feed forward controllers High performance control systems PID 2018 Benchmark Challenge Quantitative comparison Vapour compression refrigeration systems

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A flexible method for time-of-flight camera calibration using random forest 1

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1st International Conference on Smart Multimedia, ICSM 2018

作者： Xu, Chi Li, Cheng School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Bioinformatics Institute A*STAR Singapore138671 Singapore Department of Electrical and Computer Engineering University of Alberta Edmonton Canada

ISBN: (数字)9783030043759

ISBN: (纸本)9783030043742

A learning based approach is proposed to calibrate the geometric distortion of a Time-of-Flight (ToF) camera. Our method is flexible as it requires only a ToF camera and a standard camera calibration chessboard. We treat the noise model of a ToF camera as a black box, and employ random forest to automatically learn the underlying unique noise model. The geometric property of the point-cloud can be effectively restored by the learned distortion model. The method can be used in a range of computer vision applications including e.g. hand pose estimation. © 2018, Springer Nature Switzerland AG.

关键词： Calibration

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