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Supervisory control of Discrete-event Systems under Attacks

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arXiv 2017年

作者： Wakaiki, Masashi Tabuada, Paulo Hespanha, João P. Graduate School of System Informatics Kobe University Kobe657-8501 Japan Department of Electrical Engineering University of California Los AngelesCA90095-1594 United States Center for Control Dynamical-systems and Computation University of California Santa BarbaraCA93106-2560 United States

We consider a multi-adversary version of the supervisory control problem for discrete-event systems, in which an adversary corrupts the observations available to the supervisor. The supervisor’s goal is to enforce a specific language in spite of the opponent’s actions and without knowing which adversary it is playing against. This problem is motivated by applications to computer security in which a cyber defense system must make decisions based on reports from sensors that may have been tampered with by an attacker. We start by showing that the problem has a solution if and only if the desired language is controllable (in the Discrete event system classical sense) and observable in a (novel) sense that takes the adversaries into account. For the particular case of attacks that insert symbols into or remove symbols from the sequence of sensor outputs, we show that testing the existence of a supervisor and building the supervisor can be done using tools developed for the classical DES supervisory control problem, by considering a family of automata with modified output maps, but without expanding the size of the state space and without incurring on exponential complexity on the number of attacks considered. Copyright © 2017, The Authors. All rights reserved.

关键词： Game theory

Event-triggered communication and control of networked systems for multi-agent consensus

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arXiv 2017年

作者： Nowzari, Cameron Garcia, Eloy Cortés, Jorge Department of Electrical and Computer Engineering George Mason University FairfaxVA22030 United States Control Science Center of Excellence Air Force Research Laboratory Wright-Patterson AFBOH45433 United States Department of Mechanical and Aerospace Engineering University of California San DiegoCA92093 United States

This article provides an introduction to event-triggered coordination for multi-agent average consensus. We provide a comprehensive account of the motivations behind the use of event-triggered strategies for consensus, the methods for algorithm synthesis, the technical challenges involved in establishing desirable properties of the resulting implementations, and their applications in distributed control. We pay special attention to the assumptions on the capabilities of the network agents and the resulting features of the algorithm execution, including the interconnection topology, the evaluation of triggers, and the role of imperfect information. The issues raised in our discussion transcend the specific consensus problem and are indeed characteristic of cooperative algorithms for networked systems that solve other coordination tasks. As our discussion progresses, we make these connections clear, highlighting general challenges and tools to address them widespread in the event-triggered control of networked systems. Copyright © 2017, The Authors. All rights reserved.

关键词： Multi agent systems

Ultra-thin, High-efficiency Mid-Infrared Transmissive Huygens Meta-Optics

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arXiv 2017年

作者： Zheng, Hanyu Ding, Jun Zhang, Li An, Sensong Lin, Hongtao Zheng, Bowen Du, Qingyang Yin, Gufan Michon, Jerome Zhang, Yifei Fang, Zhuoran Deng, Longjiang Gu, Tian Zhang, Hualiang Hu, Juejun State Key Laboratory of Electronic Thin Films and Integrated Devices National Engineering Research Center of Electromagnetic Radiation Control Materials University of Electronic Science and Technology of China ChengduSichuan China Department of Materials Science & Engineering Massachusetts Institute of Technology CambridgeMA United States Department of Electrical & Computer Engineering University of Massachusetts Lowell LowellMA United States

The mid-infrared (mid-IR) is a strategically important band for numerous applications ranging from night vision to biochemical sensing. Unlike visible or near-infrared optical parts which are commonplace and economically available off-the-shelf, mid-IR optics often requires exotic materials or complicated processing, which accounts for their high cost and inferior quality compared to their visible or near-infrared counterparts. Here we theoretically analyzed and experimentally realized a Huygens metasurface platform capable of fulfilling a diverse cross-section of optical functions in the mid-IR. The meta-optical elements were constructed using high-index chalcogenide films deposited on fluoride substrates: the choices of wide-band transparent materials allow the design to be scaled across a broad infrared spectrum. Capitalizing on a novel two-component Huygens’ meta-atom design, the meta-optical devices feature an ultra-thin profile (λ0/8 in thickness, where λ is the free-space wavelength) and measured optical efficiencies up to 75% in transmissive mode, both of which represent major improvements over state-of-the-art. We have also demonstrated, for the first time, mid-IR transmissive meta-lenses with diffraction-limited focusing and imaging performance. The projected size, weight and power advantages, coupled with the manufacturing scalability leveraging standard microfabrication technologies, make the Huygens meta-optical devices promising for next-generation mid-IR system applications. Copyright © 2017, The Authors. All rights reserved.

关键词： Infrared devices

Determine Q-V characteristics of grid connected wind farms for voltage control using data driven analytics approach

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Determine Q-V characteristics of grid connected wind farms f...

Annual Meeting Industrial and Commercial Power Systems Technical Conference

作者： Chowdhury Andalib-Bin-Karim Xiaodong Liang Nahidul Khan Huaguang Zhang Department of Electrical and Computer Engineering Memorial University of Newfoundland St John's NL Canada New found land and Labrador Hydro System Operation & Planning Energy Control Center St John's NL Canada College of Information Science and Engineering North eastern University Shenyang Liaoning China

ISBN: (纸本)9781509057252

Due to varying and intermittent nature of wind resource, grid connected wind farms pose significant technical challenges to power grid on power quality and voltage stability. Wind farm Q-V characteristic curve at the point of interconnection (POI) can offer valuable information for voltage control actions and provide essential indication about voltage stability. Data driven analytics is a promising approach to determine characteristics of a large complex system, physical model of which is difficult to obtain. In this paper, the data driven analytics is used to determine Q-V curve of grid connected wind farms based on measurement data recorded at the POI. Different curve fitting models, such as Polynomial, Gaussian and Rational, are evaluated and best fit is determined based on different graphical and numerical evaluation metrics. A case study is conducted using field measurement data at two grid connected wind farms currently in operation in Newfoundland and Labrador, Canada. It is found that the Gaussian (degree 2) model describes the Q-V relationship most accurately for the two wind farms. The obtained functions and processed data can be used in the voltage controller design. The plotted QV curve can also be used to determine the reactive margin at the POI for voltage stability evaluation. As a generic method, the proposed approach can be employed to determine Q-V characteristic curve of any grid connected large wind farms.

关键词： Mathematical model Wind farms Voltage control Curve fitting Stability analysis Power system stability Reactive power

Selective near perfect light absorbtion by graphene monolayer using aperiodic multilayer microstructures

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arXiv 2018年

作者： Zand, Iman Dalir, Hamed Chen, Ray T. Dowling, Jonathan P. Center for Computation and Technology Louisiana State University Baton RougeLA70803 United States Hearne Institute of Theoretical Physics Department of Physics and Astronomy Louisiana State University Baton RougeLA70803 United States Omega Optics Inc. 8500 Shoal Creek Blvd. Bldg. 4 Suite 200 AustinTX78757 United States Department of Electrical and Computer Engineering University of Texas at Austin 10100 Burnet Rd. MER 160 AustinTX78758 United States New York University Shanghai Shanghai Shi200122 China Hub Petroleum 1100 Poydras St. Suite 2925 New OrleansLA70163 United States

We investigate 1D aperiodic multilayer microstructures in order to achieve near total absorption in preselected wavelengths in a graphene monolayer. Our structures are designed by a genetic optimization algorithm coupled to a transfer matrix code. Coupled mode theory (CMT) analysis, in accordance with transfer matrix method (TMM) results, indicates the existence of a critical coupling in a graphene monolayer for perfect absorptions. Our findings show that the near-total-absorption peaks are highly tunable and can be controlled simultaneously or independently in wide range of wavelengths in the near-infrared and visible. Our proposed approach is metal free and does not require surface texturing or patterning, and can be applied for other two dimensional (2D) materials. Copyright © 2018, The Authors. All rights reserved.

关键词： Monolayers

Structured light by discrete-phase orbital angular momentum holograms

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arXiv 2018年

作者： Vijayakumar, A. Rosales-Guzman, Carmelo Rai, Mani Ratnam Rosen, Joseph Minin, Oleg V. Minin, Igor V. Forbes, Andrew Department of Electrical and Computer Engineering Ben-Gurion University of the Negev P.O. Box 653 Beer-Sheva8410501 Israel School of Physics University of the Witwatersrand Private Bag X5 Johannesburg2050 South Africa Wang Da-Heng Collaborative Innovation Center for Quantum manipulation & Control Harbin University of Science and Technology Harbin150080 China National Research Tomsk State University Lenin Avenue 36 Tomsk634050 Russia National Research Tomsk Polytechnic University Lenin Avenue 30 Tomsk634050 Russia

Structured light has been created by a myriad of near- and far-field techniques and has found both classical and quantum applications. In the case of orbital angular momentum (OAM), continuous spiral phase patterns in dynamic or geometric phase are often employed with the phase patterns existing across the entire transverse plane. Here we exploit the uncertainty relation between OAM and angle to create structured OAM fields using multilevel OAM holograms. We show theoretically and experimentally that only a multilevel angular phase contour in the near-field is needed to create structured OAM light in the far-field, exploiting the reciprocal nature of angular momentum and angle. We use this approach to demonstrate exotic 3D structured light control to show the evolution of the Poynting vector in such fields and to highlight the physics underlying this phenomenon. Copyright © 2018, The Authors. All rights reserved.

关键词： Angular momentum

Driving fatigue prediction with pre-event electroencephalography (EEG) via a recurrent fuzzy neural network

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Driving fatigue prediction with pre-event electroencephalogr...

2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016

作者： Liu, Yu-Ting Wu, Shang-Lin Chou, Kuang-Pen Lin, Yang-Yin Lu, Jie Zhang, Guangquan Lin, Wen-Chieh Lin, Chin-Teng Institute of Electrical Control Engineering Taiwan Brain Research Center Taiwan Institute of Computer Science and Engineering Taiwan Department of Computer Science National Chiao-Tung University Hsinchu Taiwan Taoyuan Taiwan Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia

ISBN: (纸本)9781509006250

We propose an electroencephalography (EEG) prediction system based on a recurrent fuzzy neural network (RFNN) architecture to assess drivers' fatigue degrees during a virtual-reality (VR) dynamic driving environment. Prediction of fatigue degrees is a crucial and arduous biomedical issue for driving safety, which has attracted growing attention of the research community in the recent past. Meanwhile, combined with the benefits of measuring EEG signals facilitates, many EEG-based brain-computer interfaces (BCIs) have been developed for use in real-Time mental assessment. In the literature, EEG signals are severely blended with stochastic noise;therefore, the performance of BCIs is constrained by low resolution in recognition tasks. For this rationale, independent component analysis (ICA) is usually used to find a source mapping from original data that has been blended with unrelated artificial noise. However, the mechanism of ICA cannot be used in real-Time BCI design. To overcome this bottleneck, the proposed system in this paper utilizes a recurrent self-evolving fuzzy neural work (RSEFNN) to increase memory capability for adaptive noise cancellation when assessing drivers' mental states during a car driving task. The experimental results without the use of ICA procedure indicate that the proposed RSEFNN model remains superior performance compared with the state-of-Thearts models. © 2016 IEEE.

关键词： Electroencephalography

Distributed kalman filter in a network of linear dynamical systems

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arXiv 2017年

作者： Marelli, Damián Zamani, Mohsen Fu, Minyue Department of Control Science and Engineering State Key Laboratory of Industrial Control Technology Zhejiang University 388 Yuhangtang Road Hangzhou Zhejiang Province310058 French-Argentinean International Center for Information and Systems Sciences National Scientific and Technical Research Council Ocampo Esmeralda Rosario2000 Argentina School of Electrical Engineering and Computer Science University of Newcastle University Drive CallaghanNSW2308 Australia

This paper is concerned with the problem of distributed Kalman filtering in a network of interconnected subsystems with distributed control protocols. We consider networks, which can be either homogeneous or heterogeneous, of linear time-invariant subsystems, given in the state-space form. We propose a distributed Kalman filtering scheme for this setup. The proposed method provides, at each node, an estimation of the state parameter, only based on locally available measurements and those from the neighbor nodes. The special feature of this method is that it exploits the particular structure of the considered network to obtain an estimate using only one prediction/update step at each time step. We show that the estimate produced by the proposed method asymptotically approaches that of the centralized Kalman filter, i.e., the optimal one with global knowledge of all network parameters, and we are able to bound the convergence rate. Moreover, if the initial states of all subsystems are mutually uncorrelated, the estimates of these two schemes are identical at each time step. Copyright © 2017, The Authors. All rights reserved.

关键词： Kalman filters

Symplectomorphic registration with phase space regularization by entropy spectrum pathways.

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arXiv 2017年

作者： Galinsky, Vitaly L. Frank, Lawrence R. Center for Scientific Computation in Imaging University of California at San Diego La JollaCA92093-0854 United States Center for Functional MRI University of California at San Diego La JollaCA92093-0677 United States Electrical and Computer Engineering Department University of California at San Diego La JollaCA92093-0407 United States

The ability to register image data to a common coordinate system is a critical feature of virtually all imaging studies that require multiple subject analysis, combining single subject data from multiple modalities, or both. However, in spite of the abundance of literature on the subject and the existence of several variants of registration algorithms, their practical utility remains problematic, as commonly acknowledged even by developers of these methods because the complexity of the problem has resisted a general, flexible, and robust theoretical and computational framework. To address this issue, we present a new registration method that is similar in spirit to the current state-of-the-art technique of diffeomorphic mapping, but is more general and flexible. The method utilizes a Hamiltonian formalism and constructs registration as a sequence of symplectomorphic maps in conjunction with a novel phase space regularization based on the powerful entropy spectrum pathways (ESP) framework. The main advantage of the ESP regularized symplectomorphic approach versus the standard approach of coordinates-only diffeomorphic mapping lies in use of a common metric that remains valid even with image dependent regularization. Moreover, the fusion of the Hamiltonian framework with the ESP theory goes beyond just providing an alternative spatially varying smoothing strategy-it provides an efficient and straightforward way to combine multiple modalities. The method is demonstrated on the three different magnetic resonance imaging (MRI) modalities routinely used for human neuroimaging applications by mapping between high resolution anatomical (HRA) volumes, medium resolution diffusion weighted MRI (DW-MRI) and HRA volumes, and low resolution functional MRI (fMRI) and HRA volumes. The typical processing time for high quality mapping ranges from less than a minute to several minutes on a modern multi core CPU for typical high resolution anatomical ( 2563 voxels) MRI volumes. For val

关键词： Magnetic resonance imaging