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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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Construction of a Specialized CNC System for Thread Grinding Machines

Construction of a Specialized CNC System for Thread Grinding...

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International Russian automation Conference

作者： Georgi Martinov Ilya Kovalev Akram Al Khoury Institute of Automation and Robotics dept. Computer control systems MSTU STANKIN

ISBN: (纸本)9781538649398

The aim of this research is to construct a specialized system of thread grinding machines considering the features of thread grinding and the requirements to increase accuracy, the original structure of the control system for a thread grinder is proposed. This research will present an example of programming a software-implemented programmable logic controller to process the key press of operator's panel.

关键词： CNC system Thread grinding Soft PLC CNC system structure

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Critical technologies in the cluster of virtual and augmented reality

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IOP Conference Series: Materials Science and Engineering 2021年第1期1019卷

作者： V Zhmud A Liapidevskiy V Avrmachuk V Sayapin J N Sedinkin W Hardt Department of Automation Novosibirsk State Technical University Novosibirsk Russia General Director of Novosibirsk Institute of Program Systems Novosibirsk Russia Department of Complex Information Security of Computer Systems Tomsk State University of Control Systems and Radioelectronics Tomsk Russia Director of R&D Center of Novosibirsk Institute of Program Systems Novosibirsk Russia Vice-Director on Development of Novosibirsk Institute of Program Systems Novosibirsk Russia Department of Computer Science Technical University of Chemnitz Chemnitz Germany

The program 'Digital Economy of the Russian Federation', launched in 2019, contains virtual and augmented reality technologies in its list. Each such technology consists of many assistive technologies called sub-technologies. These assistive technologies make up a large list, while failure to obtain the required results in at least one of these technologies may lead to the fact that the integral technology will not be created. This article discusses a list of only critical assistive technologies, that is, precisely those technologies whose creation is a critical factor for creating a generalized (integral) technology. It is on these technologies that the main emphasis should be placed not only in financing their development, but also in the thorough planning of goals and objectives, in the selection of performers and in the acceptance of research results.

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Density Peak-based Pre-clustering Support Vector Machine for Multi-class Imbalanced Classification

Density Peak-based Pre-clustering Support Vector Machine for...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Zonglin Di Qi Kang Daogang Peng Mengchu Zhou Department of Control Science and Engineering Tongji University Shanghai China College of Automation Engineering Shanghai University of Electric Power Shanghai China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

Imbalanced classification using a support vector machine (SVM) is a normal but crucial problem in machine learning. Compared with binary classification, multiclass classification is much more complicated. Most existing studies on imbalanced classification using SVM focus on binary imbalanced classification; while only few of them look into imbalanced classification with multiple classes. Pre-clustering is a useful technique to prepare proper data from an imbalanced dataset for a classifier. It can be used to extract the feature of a dataset first and improve classification performance. Density peak based on Euclidean distance proves its effectiveness and generality in clustering. Motivated by this and the fact that the number of clusters is known in multi-class classification using a one-vs-rest strategy, we combine density peak clustering and SVM to propose a new pre-clustering method to perform effective imbalanced classification with multiple classes. Specifically, we transform a multi-class classification problem into several binary classification tasks. The results on 5 public datasets in terms of F-measure, G-mean and Area Under Curve (AUC) show its superiority over the original SVM and SVM with other methods including random under-sampling, Synthetic Minority Oversampling Technique, pre-clustering using K-Means and EasyEnsemble methods using either a one-vs-rest or one-vs-one strategy.

关键词： Support vector machines Feature extraction Nickel Testing Task analysis Euclidean distance Kernel

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Path planning of mobile robot based on improved DDQN

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Journal of Physics: Conference Series 2021年第1期2024卷

作者： Yang yunxiao Wangjun Zhang Hualiang Dai shilong School of Computer Science Shenyang University of Chemical Technology Shenyang 110142 China. Industrial Control Network and System Laboratory Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China. Institudes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang 110169 China.

Aiming at the problem of overestimation and sparse rewards of deep Q network algorithm in mobile robot path planning in reinforcement learning, an improved algorithm HERDDQN is proposed. Through the deep convolutional neural network model, the original RGB image is used as input, and it is trained through an end-to-end method. The improved deep reinforcement learning algorithm and the deep Q network algorithm are simulated in the same two-dimensional environment. The experimental results show that the HERDDQN algorithm solves the problem of overestimation and sparse reward better than the DQN algorithm in terms of success rate and reward convergence speed, Which shows that the improved algorithm finds a better strategy than the DQN algorithm.

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A Situation-Aware Collision Avoidance Strategy for Car-Following

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IEEE/CAA Journal of Automatica Sinica 2018年第5期5卷 1012-1016页

作者： Li Li Fellow IEEE Xinyu Peng Fei-Yue Wang ieee department of automation bnristtsinghua universityBeijing l00084China the department of automation tsinghua universityBeijing l00084China state key laboratory of management and control for complex systems institute of automationchinese academy of sciencesBeijing 100080China the driver cognition and automated driving laboratory university of waterlooWaterloo N2L 3GlCanada the department of electrical and computer engineering purdue school of engineering and technologyindiana university-purdue university indianapolisIndiana 46202-5l32USA

Abstract--In this paper, we discuss how to develop an appropriate collision avoidance strategy for car-following. This strategy aims to keep a good balance between traffic safety and efficiency while also taking into consideration the unavoidable uncertainty of position/speed perception/measurement of vehicles and other drivers. Both theoretical analysis and numerical testing results are provided to show the effectiveness of the proposed strategy. Index Terms--Collision avoidance, safety, traffic efficiency, uncertainty.

关键词： Collision avoidance safety traffic efficiency uncertainty

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Damping a pendulum's swing by string length adjustment - design and comparison of various control methods

Damping a pendulum's swing by string length adjustment - des...

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American control Conference (ACC)

作者： Milan Anderle Wim Michiels Sergej Čelikovský Tomáš Vyhlídal The Czech Academy of Sciences Institute of Information Theory and Automation (UTIA AV ČR) Prague 8 Czech Republic Department of Computer Science Heverlee Belgium Department of Instrumentation and Control Engineering Czech Technical University in Prague Czech Republic

A novel nonlinear control theory based feedback controller is proposed to damp the oscillations of the suspended load (pendulum) using the active modification of the length of the suspension string. This setting is a highly nonlinear one since the approximate linearization around the equilibrium working point is neither controllable, nor asymptotically stabilizable. The nonlinear design of the control law is therefore based on the conveniently selected control Lyapunov function. The resulting control law is then compared to the previously developed time-delay feedback control law, both in simulations and using the laboratory experimental realization of the suspended load system. Despite the fact that in the simulations the time-delay feedback control law suppresses the oscillations better than the nonlinear control law, in the experiments the performance of the time-delay feedback and of the nonlinear control law are rather similar. Moreover, the former keeps the pendulum string length oscillating, the latter stabilizes the nominal string length as well. Finally, the numerical optimization shows that the ideal damping would be provided by the impulsive-like control producing piece-wise constant string length dynamics.

关键词： Oscillators Mathematical model Damping Aerospace electronics Adaptive control Lyapunov methods Force

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An Online Approach to Physical Watermark Design

arXiv

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arXiv 2019年

作者： Liu, Hanxiao Mo, Yilin Yan, Jiaqi Xie, Lihua Johansson, Karl H. School of Electrical and Electronic Engineering Nanyang Technological University Singapore Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Department of Automation and BNRist Tsinghua University China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

This paper considers the problem of designing physical watermark signals in order to optimally detect possible replay attack in a linear time-invariant system, under the assumption that the system parameters are unknown and need to be identified online. We first provide a replay attack model, where an adversary replays the previous sensor data in order to fool the system. A physical watermarking scheme, which leverages a random control input as a watermark to detect the replay attack, is then introduced. The optimal watermark signal design problem is cast as an optimization problem, which aims to achieve the optimal trade-off between control performance and intrusion detection. An online watermarking design and system identification algorithm is provided to deal with systems with unknown parameters. We prove that the proposed algorithm converges to the optimal one and characterize the almost sure convergence rate. A numerical example and an industrial process example are provided to illustrate the effectiveness of the proposed strategy. Copyright © 2019, The Authors. All rights reserved.

关键词： Intrusion detection

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Multiple phase transitions in networks of directed networks

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Physical Review E 2019年第1期99卷 012312-012312页

作者： Xueming Liu Linqiang Pan H. Eugene Stanley Jianxi Gao Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan 430074 Hubei China Department of Physics Center for Polymer Studies Boston University Boston Massachusetts 02215 USA Department of Computer Science Rensselaer Polytechnic Institute Troy New York 12180 USA

The robustness in real-world complex systems with dependency connectivities differs from that in isolated networks. Although most complex network research has focused on interdependent undirected systems, many real-world networks—such as gene regulatory networks and traffic networks—are directed. We thus develop an analytical framework for examining the robustness of networks made up of directed networks of differing topologies. We use it to predict the phase transitions that occur during node failures and to generate the phase diagrams of a number of different systems, including treelike and random regular (RR) networks of directed Erdős-Rényi (ER) networks and scale-free networks. We find that the the phase transition and phase diagram of networks of directed networks differ from those of networks of undirected networks. For example, the RR networks of directed ER networks show a hybrid phase transition that does not occur in networks of undirected ER networks. In addition, system robustness is affected by network topology in networks of directed networks. As coupling strength q increases, treelike networks of directed ER networks change from a second-order phase transition to a first-order phase transition, and RR networks of directed ER networks change from a second-order phase transition to a hybrid phase transition, then to a first-order phase transition, and finally to a region of collapse. We also find that heterogenous network systems are more robust than homogeneous network systems. We note that there are multiple phase transitions and triple points in the phase diagram of RR networks of directed networks and this helps us understand how to increase network robustness when designing interdependent infrastructure systems.

关键词： Attacks on networks Cascades Continuous phase transition Discontinuous phase transition Network phase transitions Percolation phase transition Random attacks Robustness Topological phase transition

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

A flexible method for time-of-flight camera calibration usin...

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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: (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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