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An Algorithm for On-Line Image Segmentation of Multiple Paper Defects Based on Fast Two-Dimensional Threshold Method

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Palpu Chongi Gisul/Journal of Korea Technical Association of the Pulp and Paper Industry 2020年第4期52卷 28-37页

作者： Qu, Yun-Hui Tang, Wei Feng, Bo Department of Electric and Control Engineering Shaanxi University of Science & Technology Shaanxi Xi’an710021 China Computer Teaching and Research Section Xi’an Medical University Shaanxi Xi’an710021 China

The two-dimensional threshold segmentation algorithm is time-consuming and cannot detect multiple paper defects. Considering these problems, a fast two-dimensional threshold method for on-line segmentation of multiple paper defects was proposed. The image subtraction operation was used first to segment the image with multiple paper defects. Then dividing two-dimensional threshold into two one-dimensional thresholds was used to accelerate the segmentation. At the same time, according to the gray distribution characteristics of the paper defect image after subtraction, the search range of the threshold was narrowed, and the selection of the optimal threshold was further accelerated. Experimental results showed that the algorithm proposed in this paper can accurately and quickly detect multiple paper defects, and could be effectively used for real-time detection of the paper production process. © 2020 Korean Technical Assoc. of the Pulp and Paper Industry. All rights reserved.

关键词： Defects

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Unified resilience model using deep learning for assessing power system performance

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Heliyon 2025年第4期11卷 e42802页

作者： Artemchuk, Volodymyr Garbuz, Iurii Jamil Alsayaydeh, Jamil Abedalrahim Shkarupylo, Vadym Oliinyk, Andrii Bin Yusof, Mohd Faizal Herawan, Safarudin Gazali Department of Mathematical and Econometric Modelling G.E. Pukhov Institute for Modelling in Energy Engineering of the NAS of Ukraine Kyiv Ukraine Department of Environmental Protection Technologies and Radiation Safety Center for Information-analytical and Technical Support of Nuclear Power Facilities Monitoring of the NAS of Ukraine Kyiv Ukraine Department of Іnformation Systems in Economics Kyiv National Economic University Named After Vadym Hetman Kyiv Ukraine Department of Computerized Control System National Aviation University Kyiv Ukraine Department of Engineering Technology Fakulti Teknologi Dan Kejuruteraan Elektronik Dan Komputer (FTKEK) Universiti Teknikal Malaysia Melaka (UTeM) Melaka 76100 Malaysia Department of Computer Systems Networks and Cybersecurity of the National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Department of Software Tools Faculty of Computer Science and Technology Zaporizhzhia Polytechnic National University Zaporizhzhia Ukraine Research Section Faculty of Resilience Rabdan Academy Abu Dhabi United Arab Emirates Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta 11480 Indonesia

Energy resilience in renewable energy sources dissemination components such as batteries and inverters is crucial for achieving high operational fidelity. Resilience factors play a vital role in determining the performance of power systems, regardless of their operating environment and interruptions. This article introduces a Unified Resilience Model (URM) using Deep Learning (DL) to enhance power system performance. The proposed model analyzes environmental factors impacting the resilience of batteries and energy storage devices. This deep learning approach trains performance-impacting factors using previously known low resilience drain data. The learning output is utilized to augment various strengthening factors, thereby improving resilience. Drain mitigation and performance improvements are combined for direct impact verification. This process validates the model's fidelity in enhancing power system performance, with a specific focus on the impact of weather factors. © 2025 The Authors

关键词： Deep learning Energy resilience Fidelity Weather impact

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A secure state estimation algorithm for nonlinear systems under sensor attacks

arXiv

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arXiv 2020年

作者： Chong, Michelle S. Sandberg, Henrik Hespanha, João P. Control Systems Technology section Department of Mechanical Engineering Eindhoven University of Technology Netherlands Division of Decision and Control Systems KTH Royal Institute of Techonology Sweden Electrical and Computer Engineering Department University of California Santa Barbara United States

The state estimation of continuous-time nonlinear systems in which a subset of sensor outputs can be maliciously controlled through injecting a potentially unbounded additive signal is considered in this paper. Analogous to our earlier work for continuous-time linear systems in [1], we term the convergence of the estimates to the true states in the presence of sensor attacks as ‘observability under M attacks’, where M refers to the number of sensors which the attacker has access to. Unlike the linear case, we only provide a sufficient condition such that a nonlinear system is observable under M attacks. The condition requires the existence of asymptotic observers which are robust with respect to the attack signals in an input-to-state stable sense. We show that an algorithm to choose a compatible state estimate from the state estimates generated by the bank of observers achieves asymptotic state reconstruction. We also provide a constructive method for a class of nonlinear systems to design state observers which have the desirable robustness property. The relevance of this study is illustrated on monitoring the safe operation of a power distribution network. Copyright © 2020, The Authors. All rights reserved.

关键词： State estimation

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control design and Lyapunov Functions via Bernstein Approximations: Exact Results ⁎

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IFAC-PapersOnLine 2020年第2期53卷 6459-6464页

作者： Tareq Hamadneh Nikolaos Athanasopoulos Rafael Wisniewski Al Zaytoonah University of Jordan Department of Mathematics Amman Jordan School of Electronics Electrical Engineering and Computer Science Queen’s University Belfast Northern Ireland Section of Automation and Control Aalborg University 9220 Aalborg East Denmark

We study the control problem for polynomial continuous-time dynamical systems. We consider polynomial Lyapunov functions and controllers, both parameterised in Bernstein form. Specifically, we present necessary and sufficient conditions for existence of polynomial controllers and Lyapunov functions of some maximum degree, providing at the same time explicit upper bounds on the degree of the involved Bernstein polynomials. The formulated conditions are a set of algebraic inequalities, in the space of Bernstein coefficients.

关键词： Bernstein polynomials control design certificates of positivity Lyapunov stability control Lyapunov Functions polynomial systems

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Characterizing and mitigating coherent errors in a trapped ion quantum processor using hidden inverses

arXiv

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arXiv 2022年

作者： Majumder, Swarnadeep Yale, Christopher G. Morris, Titus Lobser, Daniel S. Burch, Ashlyn D. Chow, Matthew N.H. Revelle, Melissa C. Clark, Susan M. Pooser, Raphael C. Duke Quantum Center Duke University DurhamNC27701 United States Department of Electrical and Computer Engineering Duke University DurhamNC27708 United States Sandia National Laboratories AlbuquerqueNM87123 United States Quantum Information Science Section Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Physics and Astronomy University of New Mexico AlbuquerqueNM87131 United States Center for Quantum Information and Control University of New Mexico AlbuquerqueNM87131 United States

Quantum computing testbeds exhibit high-fidelity quantum control over small collections of qubits, enabling performance of precise, repeatable operations followed by measurements. Currently, these noisy intermediate-scale devices can support a sufficient number of sequential operations prior to decoherence such that near term algorithms can be performed with proximate accuracy (like chemical accuracy for quantum chemistry problems). While the results of these algorithms are imperfect, these imperfections can help bootstrap quantum computer testbed development. Demonstrations of these algorithms over the past few years, coupled with the idea that imperfect algorithm performance can be caused by several dominant noise sources in the quantum processor, which can be measured and calibrated during algorithm execution or in post-processing, has led to the use of noise mitigation to improve typical computational results. Conversely, benchmark algorithms coupled with noise mitigation can help diagnose the nature of the noise, whether systematic or purely random. Here, we outline the use of coherent noise mitigation techniques as a characterization tool in trapped-ion testbeds. We perform model-fitting of the noisy data to determine the noise source based on realistic physics focused noise models and demonstrate that systematic noise amplification coupled with error mitigation schemes provides useful data for noise model deduction. Further, in order to connect lower level noise model details with application specific performance of near term algorithms, we experimentally construct the loss landscape of a variational algorithm under various injected noise sources coupled with error mitigation techniques. This type of connection enables application-aware hardware code-sign, in which the most important noise sources in specific applications, like quantum chemistry, become foci of improvement in subsequent hardware generations. © 2022, CC BY.

关键词： Testbeds

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Traceable random numbers from a nonlocal quantum advantage

arXiv

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arXiv 2024年

作者： Kavuri, Gautam A. Palfree, Jasper Reddy, Dileep V. Zhang, Yanbao Bienfang, Joshua C. Mazurek, Michael D. Alhejji, Mohammad A. Siddiqui, Aliza U. Cavanagh, Joseph M. Dalal, Aagam Abellán, Carlos Amaya, Waldimar Mitchell, Morgan W. Stange, Katherine E. Beale, Paul D. Brandão, Luís T.A.N. Booth, Harold Peralta, René Nam, Sae Woo Mirin, Richard P. Stevens, Martin J. Knill, Emanuel Shalm, Lynden K. Department of Physics University of Colorado BoulderCO80309 United States The National Institute of Standards and Technology BoulderCO80305 United States Quantum Information Science Section Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Joint Quantum Institute National Institute of Standards and Technology University of Maryland 100 Bureau Drive GaithersburgMD20899 United States Center for Quantum Information and Control University of New Mexico AlbuquerqueNM87131 United States Department of Electrical Computer and Energy Engineering University of Colorado BoulderCO80309 United States Physical Measurement Laboratory National Institute of Standards and Technology GaithersburgMD20899 United States Quside Technologies S.L. Castelldefels Barcelona Spain ICFO-Institut de Ciencies Fotoniques The Barcelona Institute of Science and Technology Castelldefels Barcelona08860 Spain ICREA - Institució Catalana de Recerca i Estudis Avançats Barcelona08010 Spain Department of Mathematics University of Colorado BoulderCO80309 United States GaithersburgMD20899 United States Information Technology Laboratory National Institute of Standards and Technology GaithersburgMD20899 United States Physical Measurement Laboratory National Institute of Standards and Technology BoulderCO80305 United States Center for Theory of Quantum Matter University of Colorado BoulderCO80305 United States Applied and Computational Mathematics Division National Institute of Standards and Technology BoulderCO80305 United States Quantum Engineering Initiative Department of Electrical Computer and Energy Engineering University of Colorado BoulderCO80309 United States

The unpredictability of random numbers is fundamental to both digital security [1, 2] and applications that fairly distribute resources [3, 4]. However, existing random number generators have limitations—the generation processes cannot be fully traced, audited, and certified to be unpredictable. The algorithmic steps used in pseudorandom number generators [5] are auditable, but they cannot guarantee that their outputs were a priori unpredictable given knowledge of the initial seed. Device-independent quantum random number generators [6–9] can ensure that the source of randomness was unknown beforehand, but the steps used to extract the randomness are vulnerable to tampering. Here, for the first time, we demonstrate a fully traceable random number generation protocol based on device-independent techniques. Our protocol extracts randomness from unpredictable non-local quantum correlations, and uses distributed intertwined hash chains to cryptographically trace and verify the extraction process. This protocol is at the heart of a public traceable and certifiable quantum randomness beacon that we have launched [10]. Over the first 40 days of operation, we completed the protocol 7434 out of 7454 attempts—a success rate of 99.7%. Each time the protocol succeeded, the beacon emitted a pulse of 512 bits of traceable randomness. The bits are certified to be uniform with error times actual success probability bounded by 2−64. The generation of certifiable and traceable randomness represents one of the first public services that operates with an entanglement-derived advantage over comparable classical approaches. Copyright © 2024, The Authors. All rights reserved.

关键词： Random number generation

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Nonlinear Modeling of the Subcritical Boiler-turbine System with Stochastic Differential Equations∗

Nonlinear Modeling of the Subcritical Boiler-turbine System ...

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2019 IEEE International Conference on Power Data Science, ICPDS 2019

作者： Du, Ming Xia, Jie Qian, Yonggui Li, Xiaobin Cai, Guoyuan Liu, Rui School of Control and Computer Engineering North China Electric Power University Beijing China Huaihu Coal and Electricity Co. Ltd. Tianji Power Plant Huainan Anhui Province232000 China China Railway Beijing Bureau Group Co. Ltd. Beijing West Power Section Official Beijing China

ISBN: (纸本)9781728137759

With the large-scale renewable energy integrated into power system, the optimization of coordinated control system (CCS) is increasingly crucial. The dynamics of subcritical boiler-turbine system have been studied through kinds of modeling methods. But the ordinary differential equations (ODEs) are used in previous studies mainly, which can not reflect the uncertainties in this system. In this work, the uncertainties in subcritical boiler-turbine system had been analyzed and the dynamics had been described with stochastic differential equations (SDEs). Great improvements of boiler- turbine system model can be seen in the simulations. This model can be the platform to study stochastic model predictive control in CCS. © 2019 IEEE.

关键词： Ordinary differential equations

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Guidance Vector Field Encoding based on Contraction Analysis 16

Guidance Vector Field Encoding based on Contraction Analysis

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16th European control Conference, ECC 2018

作者： Wu, Chengshuai Chen, Jian Jeltsema, DImitri Dai, And Chenxi State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China Section Control Systems Engineering HAN University of Applied Science P.O. Box 2217 Arnhem6802 CE Netherlands Department of Electrical and Computer Engineering Ohio State University Columbus43210 United States

ISBN: (纸本)9783952426982

The guidance vector field encoding problem is revisited via exploiting the recently developed differential Lyapunov framework for contraction analysis. In control applications, a designed guidance vector field is utilized to guide a particle (such as a robot, or an end actuator) to converge to and circulate along a target curve, such as robot navigation, or motion planing. This paper proposes some new methods for guidance vector filed encoding. The methods analyze the guidance vector field encoding problem from a theoretical perspective providing insights into the problem, and it shows that the contraction analysis is a natural theoretical tool for guidance vector encoding. Furthermore, the differences and relations between the proposed result and the previous methods are discussed. Simulation examples are presented to illustrate the effectiveness of the proposed methods. © 2018 European control Association (EUCA).

关键词： Robots

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Design of ADRC for Second-Order Mechanical Systems without Time-Derivatives in the Tracking controller

Design of ADRC for Second-Order Mechanical Systems without T...

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American control Conference

作者： M. Ramirez-Neria R. Madonski A. Luviano-Juarez Z. Gao H. Sira-Ramirez Mechatronics Departament Uni¬versidad Politécnica del Valle de Mexico Tultitlán Es¬tado de Méixico Energy Electricity Research Center Inter¬national Energy College Jinan University Zhuhai P. R. China UPIITA-IPN Mexico City Mexico Department of Electrical and Computer Engineering Center for Advanced Control Technologies Cleveland State University Cleveland Ohio USA Electrical Engineer¬ing Department of Cinvestav-IPN Mechatronics Section Mexico City

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

In this article, the problem of designing Active Disturbance Rejection control (ADRC) for a class of second-order mechanical systems, expressed with Euler-Lagrange equations, is studied. A specific and practically motivated case is considered here, namely trajectory tracking task without the use of signal time-derivatives in the tracking controller. A general solution is proposed showing how to synthesize and tune the observer and the controller parts of the ADRC scheme. A special Extended State Observer is used in the design and here it takes the form of a Generalized Proportional Integral Observer (GPIO), which uses a Taylor series approximation of the total disturbance. A set of experimental results, obtained using a two degree-of-freedom robotic manipulator, shows the effectiveness of the proposed governing scheme in terms of trajectory realization and disturbance rejection without the use of signal time-derivatives in the controller.

关键词： Observers Manipulators Mechanical systems Trajectory tracking Trajectory Electronic mail

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Nonlinear Modeling of the Subcritical Boiler-turbine System with Stochastic Differential Equations*

Nonlinear Modeling of the Subcritical Boiler-turbine System ...

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IEEE International Conference on Power Data Science (ICPDS)

作者： Ming Du Jie Xia Yonggui Qian Xiaobin Li Guoyuan Cai Rui Liu School of control and computer engineering North China Electric Power University Beijing China Huaihu Coal and Electricity Co. Ltd. Huainan Anhui Province China China Railway Beijing Bureau Group Co. Ltd. Beijing West Power Section official Beijing China

ISBN: (数字)9781728137759

ISBN: (纸本)9781728137766

关键词： Mathematical model Load modeling Coal Boilers Turbines Analytical models

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