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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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A Review of Collaborative Innovation among University,Industry,and Government from the Perspective of Coupling

A Review of Collaborative Innovation among University,Indust...

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作者： Genping Yu Di Chen Zuoyong Li Zhongyan Lin Internet Innovation Research Center-the College's Research Base of Humanities and Social Science in Fujian Province Minjiang University Scientific Research Administrative Department of Minjiang University College of Computer and Control Engineering Minjiang University

University is not only the primary unit of training talents but also an essential part of the national innovation *** paper will research the university industry-academia-research collaboration literature review,through further statement and explanation of the industry-academia-research collaboration *** the coupling relationship between the three major innovations of universities,industries,and governments,enhance the contribution of university science and technology innovation application ability and service society *** promote the construction of regional science and technology cooperation platform and the coordinated development of multilateral technology systems.

关键词： University Industry Government Collaborative innovation

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Scalable block-diagonal locality-constrained projective dictionary learning

arXiv

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arXiv 2019年

作者： Zhang, Zhao Jiang, Weiming Zhang, Zheng Li, Sheng Liu, Guangcan Qin, Jie School of Computer Science School of Artificial Intelligence Hefei University of Technology China School of Computer Science and Technology Soochow University China School of Information Technology and Electrical Engineering University of Queensland Australia Department of Computer Science University of Georgia United States School of Information and Control Nanjing University of Information Science and Technology China Computer Vision Laboratory ETH Zurich Switzerland

We propose a novel structured discriminative blockdiagonal dictionary learning method, referred to as scalable Locality-Constrained Projective Dictionary Learning (LC-PDL), for efficient representation and classification. To improve the scalability by saving both training and testing time, our LC-PDL aims at learning a structured discriminative dictionary and a block-diagonal representation without using costly l0/l1-norm. Besides, it avoids extra time-consuming sparse reconstruction process with the well-trained dictionary for new sample as many existing models. More importantly, LC-PDL avoids using the complementary data matrix to learn the sub-dictionary over each class. To enhance the performance, we incorporate a locality constraint of atoms into the DL procedures to keep local information and obtain the codes of samples over each class separately. A block-diagonal discriminative approximation term is also derived to learn a discriminative projection to bridge data with their codes by extracting the special block-diagonal features from data, which can ensure the approximate coefficients to associate with its label information clearly. Then, a robust multiclass classifier is trained over extracted block-diagonal codes for accurate label predictions. Experimental results verify the effectiveness of our algorithm. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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Fault Detection and Isolation for a 3-DOF Helicopter with Sliding Mode Strategies 15

Fault Detection and Isolation for a 3-DOF Helicopter with Sl...

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15th International Workshop on Variable Structure Systems, VSS 2018

作者： Perez, U. Capello, E. Punta, E. Perea, J. Fridman, L. Department of Control and Robotics Division of Electrical Engineering Engineering Faculty National Autonomous University of Mexico C.P. 04510 Mexico Politecnico di Torino Department of Mechanical and Aerospace Engineering Torino10129 Italy National Research Council of Italy CNR-IEIIT Institute of Electronics Computer and Telecommunication Engineering Torino Italy

ISBN: (纸本)9781538664391

This paper analyzes the problem of detection and isolation of faults in the actuators of a 3-Degree-of-Freedom (3-DOF) helicopter by a residual-based approach. A third-order sliding mode differentiator is designed for the evaluation of the residuals. Moreover, two sliding mode controllers are suitably designed to stabilize the angular positions and velocities: (i) a super twisting control system and (ii) a continuous twisting control system. The performance of the designed controllers and the effectiveness of the residual-based method are illustrated by simulations. © 2018 IEEE.

关键词： controllers

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A Modularized Design for Output Synchronization of LTI Dynamical Networks with Communication Delays

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SICE Journal of control, Measurement, and System Integration 2018年第6期11卷 495-501页

作者： Hayato Dan Takeshi Hatanaka Hyungbo Shim Department of Systems and Control Engineering Tokyo Institute of Technology Division of Electrical Electronic and Information Engineering Osaka University ASRI Department of Electrical and Computer Engineering Seoul National University

In this paper, we address output synchronization for a network of heterogeneous agents with linear time invariant single-input-single-output dynamics in the presence of communication delays. To this end, we present a three-stage modularized design procedure: (i) a parallel feedforward compensator is designed to convert the dynamics to a minimum-phase system with relative degree one, (ii) the resulting system is then transformed into a feedback equivalent to a passive system, and (iii) the agents are interconnected based on a passivity-based output synchronization law. The benefit of the present control scheme is that not only implementation but also the design stage of the controller is distributed, namely the agents do not need to know the entire network structure. The present solution is then shown to achieve output synchronization. We finally demonstrate the present controller through simulation.

关键词： output synchronization communication delay parallel feedforward compensator passivity

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OER: Six Perspectives on Global Misconceptions and Challenges

OER: Six Perspectives on Global Misconceptions and Challenge...

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IEEE International Conference on Teaching, Assessment and Learning for engineering (TALE)

作者： Dave Towey Sorel Reisman Henry Chan Claudio Demartini Edmundo Tovar Tiziana Margaria School of Computer Science University of Nottingham Ningbo China Ningbo People’s Republic of China Department of Information Systems and Decision Sciences California State University Fullerton Fullerton U.S.A. Department of Computing The Hong Kong Polytechnic University Hong Kong China Control & Computer Engineering Department Politecnico di Torino Turin Italy School of Computer Engineers Universidad Politécnica de Madrid Madrid Spain Department of Computer Science and Information Systems University of Limerick Limerick Ireland

ISBN: (数字)9781728126654

ISBN: (纸本)9781728126661

Open Educational Resources (OERs) are freely accessible materials for teaching, learning, and research that have been made available such that they can be freely used, modified, and shared. Prompted by the potential positive impact that OERs can have, a growing community of OER enthusiasts has been advocating for their adoption in higher education, and elsewhere. The growing demand for computer science education and training (especially in areas related to artificial intelligence, machine learning, and big data) has led to speculation as to how OERs may be best leveraged to support such teaching and learning. The recent occasion of an international OER workshop at the 2019 IEEE Conference on computers, Software and Applications (COMPSAC) allowed for six OER enthusiasts, all with extensive OER experience, to reflect on the status of OER adoption and understanding. These reflections, addressing misconceptions and challenges, form the basis for this paper.

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Metamorphosis of discontinuity lines and rectification of magnetic flux avalanches in the presence of noncentrosymmetric pinning forces

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Physical Review B 2021年第22期103卷 224514-224514页

作者： M. Motta L. Burger Lu Jiang J. D. González Acosta Ž. L. Jelić F. Colauto W. A. Ortiz T. H. Johansen M. V. Milošević C. Cirillo C. Attanasio Cun Xue A. V. Silhanek B. Vanderheyden Departamento de Física Universidade Federal de São Carlos 13565-905 São Carlos São Paulo Brazil Montefiore Research Unit Department of Electrical Engineering and Computer Science Université de Liège 4000 Sart Tilman Belgium School of Aeronautics Northwestern Polytechnical University Xi'an 710072 China Facultad de Ingeniería Universidad del Magdalena Santa Marta Colombia Departement Fysica Universiteit Antwerpen Groenenborgerlaan 171 B-2020 Antwerpen Belgium Nokia Bell Labs Antwerp Belgium Department of Physics University of Oslo POB 1048 Blindern 0316 Oslo Norway CNR-SPIN c/o Università degli Studi di Salerno I-84084 Fisciano (Sa) Italy Dipartimento di Fisica “E.R. Caianiello” Università degli Studi di Salerno I-84084 Fisciano (Sa) Italy School of Mechanics Civil Engineering and Architecture and MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical University Xi'an 710072 China Experimental Physics of Nanostructured Materials Q-MAT CESAM Université de Liège B-4000 Sart Tilman Belgium

Considering a noncentrosymmetric pinning texture composed of a square array of triangular holes, the magnetic flux penetration and expulsion are investigated experimentally and theoretically. A direct visualization of the magnetic landscape obtained using a magneto-optical technique on a Nb film is complemented by a multiscale numerical modeling. This combined approach allows the magnetic flux dynamics to be identified from the single flux quantum limit up to the macroscopic electromagnetic response. Within the theoretical framework provided by time-dependent Ginzburg-Landau simulations, an estimation of the in-plane current anisotropy is obtained and its dependence with the radius of the curvature of hole vertices is addressed. These simulations show that current crowding plays an important role in channeling the flux motion, favoring hole-to-hole flux hopping rather than promoting interstitial flux displacement in between the holes. The resulting anisotropy of the critical current density gives rise to a distinct pattern of discontinuity lines for increasing and decreasing applied magnetic fields, in sharp contrast to the invariable patterns reported for centrosymmetric pinning potentials. This observation is partially accounted for by the rectification effect, as demonstrated by finite-element modeling. At low temperatures, where magnetic field penetration is dominated by thermomagnetic instabilities, highly directional magnetic flux avalanches with a fingerlike shape are observed to propagate along the easy axis of the pinning potential. This morphology is reproduced by numerical simulations. Our findings demonstrate that anisotropic pinning landscapes and, in particular, ratchet potentials produce subtle modifications to the critical state field profile that are reflected in the distribution of discontinuity lines.

关键词： Flux pinning Magneto-optical effect Monolayer films Superconductors Finite-element method Landau-Ginzburg theory

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Oscillation Detection and Diagnosis in Process Industries by Pattern Recognition Technique

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IFAC-PapersOnLine 2019年第1期52卷 299-304页

作者： Jônathan W.V. Dambros Marcelo Farenzena Jorge O. Trierweiler Group of Intensification Modeling Simulation Control and Optimization of Processes (GIMSCOP) Chemical Engineering Department Federal University of Rio Grande do Sul (UFRGS) R. Eng. Luiz Englert s/n Campus Central Porto Alegre RS Brazil Department of Computer Science University of Kaiserslautern 67663 Kaiserslautern Deutschland

Oscillation in control loops is a frequent problem faced in process industries. It deviates the process variables from their desired condition, affecting negatively plant productivity. To guarantee profitability, oscillation must be detected, diagnosed, and, finally, eliminated. Dozens of automatic detection and diagnosis techniques have been proposed over the last years. However, the application to real industrial data reveals low efficiencies, which indicates that the techniques require improvement. This work presents a new method for oscillation detection and diagnosis. The technique classifies the loops based on the shape of the PV(OP) diagram by a pattern recognition approach, where the model is trained with simulated examples that cover a large range of processes and different conditions found in industrial data, such as noise and disturbance presence. The performance of the proposed technique is compared to well-established oscillation detection and diagnosis methods, returning better results.

关键词： Oscillation detection diagnosis process control fault detection diagnosis pattern recognition process monitoring

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The multi-harmonic signal frequencies estimation in finite time

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Journal of Physics: Conference Series 2021年第1期1864卷

作者： A. O. Vediakova A. A. Vedyakov A. A. Pyrkin A. A. Bobtsov V. S. Gromov Department of Computer Applications and Systems St. Petersburg State University 7/9 Universitetskaya nab. St. Petersburg 199034 Russia Department of Control Systems and Informatics ITMO University 49 Kronverkskiy pr. St. Petersburg 197101 Russia Laboratory 'Control of Complex Systems' Institute of Problems of Mechanical Engineering V.O. 61 Bolshoy pr. St. Petersburg 199178 Russia

The paper presents a method to estimate the frequencies of a multi-harmonic signal in finite time. We use parameterization based on applying delay operators to a measurable signal. The result is a linear regression model with an unknown vector which depends on the signal parameters. We use Dynamic Regressor Extension and Mixing method to replace the n-th order regression model with scalar regressions. After that, we estimate the parameters separately using the standard gradient descent method. In the last step, we find algebraically the finite-time parameter estimates. The set of numerical simulations demonstrates the efficiency of the proposed approach.

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Fast online reinforcement learning control using state-space dimensionality reduction

arXiv

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arXiv 2019年

作者： Sadamoto, Tomonori Chakrabortty, Aranya Imura, Jun-Ichi Department of Mechanical and Intelligent Systems Engineering Graduate School of Informatics and Engineering University of Electro Communications 1-5-1 Chofugaoka Chofu Tokyo182-8585 Japan Electrical and Computer Engineering North Carolina State University RaleighNC27695 United States Department of Systems and Control Engineering Graduate School of Engineering Tokyo Institute of Technology Oh-Okayama Meguro Tokyo2-12-1 Japan

Reinforcement Learning (RL) is an effective way of designing model-free linear quadratic regulator (LQR) controller for linear time-invariant (LTI) networks with unknown state-space models. However, when the network size is large, conventional RL can result in unacceptably long learning time. In this paper we resolve this problem by developing an alternative approach for RL-based LQR that combines dimensionality reduction with RL theory. The approach is to construct a compressed state vector by projecting the measured state through a projective matrix. This matrix is constructed from the state measurements, and can be viewed as an empirical controllability gramian that captures the level of redundancy in the controllability of the open-loop network model. Next, a RL-controller is learned using the reduced-dimensional state instead of the original state such that the resultant cost is close to the optimal LQR cost. Numerical benefits as well as the cyber-physical implementation benefits of the proposed approach are verified using illustrative examples including an example of wide-area control of the IEEE benchmark power system. Copyright © 2019, The Authors. All rights reserved.

关键词： controllers

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