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2022 International Conference Laser Optics, ICLO 2022

作者： Oliveira, L.M. Goncalves, T.M. Botelho, A.R. Martins, I.S. Silva, H.F. Carneiro, I. Carvalho, S. Henrique, R. Tuchin, V.V. Porto Portugal Center of Innovation in Engineering and Industrial Technology Isep Porto Portugal Department of Electrical and Computer Engineering Porto University-School of Engineering Porto Portugal Department of Pathology and Cancer Biology and Epigenetics Group Portuguese Oncology Institute of Porto Porto Portugal Porto Portugal Viana do Castelo Portugal Dept. of Pathol. and Molecular Immunology Porto University-Institute of Biomedical Sciences Abel Salazar Porto Portugal Science Medical Center Saratov State University Saratov Russia Laboratory of Laser Molecular Imaging and Machine Learning National Research Tomsk State University Tomsk Russia Laboratory of Laser Diagnostics of Technical and Living Systems Institute of Precision Mechanics and Control Frc-Saratov Scientific Centre-of the Russian Academy of Sciences Saratov Russia

ISBN: (纸本)9781665466646

The direct calculation of the absorption coefficient spectra of various tissues from spectral measurements allowed to retrieve the contents of melanin and lipofuscin. In the rabbit brain cortex, 1.8 times higher melanin content is explained by the neuron degeneration process. Similar melanin and lipofuscin contents were found in the rabbit pancreas as a result of the tissue aging process. The conversion of 83 % of the melanin in the human normal kidney into lipofuscin in the cancer kidney indicates that lipofuscin can be considered a kidney cancer marker in humans. © 2022 IEEE.

关键词： Tissue

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Two TS-Fuzzy controllers based Direct Torque control of 5-Phase Induction Motor

Two TS-Fuzzy Controllers based Direct Torque Control of 5-Ph...

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International Conference on Power Electronic Drives

作者： Malik G. Al-Ghanimi Omar Hanif Mahit V. Jain A. Siva Kumar Ramana Rao M. V R. Kavin Siva Ganesh Malla Jagan Mohana Rao Malla Md. Amzad Hossain Technical institute of Al-Mussaib Al-Furat Al-Awsat Technical University Iraq Dept. of Automatic Control and Systems Engineering The University of Sheffield Sheffield The United Kingdom Sigma Institute of Engineering Vadodara India Department of EEE Panimalar Engineering College Chennai Tamilnadu India University College of Engineering Osmania University Hyderabad India Sri Krishna College of Engineering & Technology Coimbatore India CPGC Pvt. Ltd. Visakhapatnam India Geethanjali College of Engineering and Technology Hyderabad Telangana India Institute of Theoretical Electrical Engineering Ruhr University Bochum (RUB) Germany

The interest on five phase induction motor drives is gradually increasing due to its wide variety of applications including electric vehicles, high compressor systems, ship propulsion etc. The designing of a proper controller to make 5-phase induction motor based electric drive is playing a vital role for many usages among many controllers, a direct torque controller (DTC) is a famous technique to achieve motor torque with fewer ripples. Moreover, Takagi Suguno - Fuzzy (TS-Fuzzy) controllers can provide fast response under rapid changes of inputs. Therefore, TS-Fuzzy based DTC of 5-phase induction motor drive is proposed in this paper. Further, the space vector modulation technique is implemented for obtaining proper pulse sequence for 5-phase inverter to drive the motor. In order to achieve smooth control of both torque and flux, two fuzzy logic controllers are deployed on the DTC of the motor. For better illustration, responses of the proposed TS-Fuzzy based DTC of 5-phase induction motor are compared with 3-phase motor. The proposed method is simulated and presented in this paper to analyze the performance of the proposed method under various conditions.

关键词： Induction motor drives Support vector machines Fuzzy logic Torque Torque control Modulation Switches

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GRID-FOLLOWING THREE-PHASE INVERTER WITH RMS CURRENT-LIMITING PROPERTY

GRID-FOLLOWING THREE-PHASE INVERTER WITH RMS CURRENT-LIMITIN...

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The 12th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MEDPOWER 2020)

作者： P. Skentzos G. C. Konstantopoulos Dept. of Automatic Control and Systems Engineering The University of Sheffield Mappin Street S1 3JD Sheffield U.K.

A novel nonlinear controller that inherently limits the RMS value of a three-phase grid-following inverter current is presented in this paper. Using the dynamic model of the inverter in the rotating dq reference frame, a nonlinear control scheme is formulated to ensure accurate real and reactive power regulation with RMS current limitation that avoids the use of saturation units with upper/lower limit adaptation, as commonly used in the existing approaches. In particular, it is analytically proven by using fundamental nonlinear systems theory, that the RMS value of the inverter current will never violate a given maximum value, both during the transient response and at the steady-state. Moreover, a detailed root locus analysis is provided to guarantee the asymptotic stability of the desired equilibrium point for the closed-loop system. Finally, to validate the proposed controller performance, simulation results of a grid-following three-phase inverter equipped with the proposed control approach are presented under both normal and unrealistic values of the real and reactive power setpoints.

关键词： invertors control system synthesis nonlinear control systems transient response asymptotic stability closed loop systems

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Optimal time-domain moment matching with partial placement of poles and zeros

Optimal time-domain moment matching with partial placement o...

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European control Conference (ECC)

作者： T. C. Ionescu O. V. Iftime I. Necoara Dept. of Automatic Control & Systems Eng. Politehnica Univ. of Bucharest Bucharest Romania Department of Economics Econometrics and Finance Faculty of Economics and Business University of Groningen Groningen The Netherlands Department of Automatic Control and Systems Engineering University Politehnica Bucharest Bucharest Romania

ISBN: (数字)9783907144022

ISBN: (纸本)9781728188133

In this paper we consider a minimal, linear, time-invariant (LTI) system of order n, large. Our goal is to compute an approximation of order ν 2 norm of the approximation error. For this, in the family of ν order parametrized models that match ν moments we impose ℓ+k linear constraints yielding a subfamily of models with ℓ poles and k zeros imposed. Then, in the subfamily of ν order models matching ν moments, with ℓ poles and k zeros imposed we propose an optimization problem that provides the model yielding the minimal H 2 -norm of the approximation error. We analyze the first-order optimality conditions of this optimization problem and compute explicitly the gradient of the objective function in terms of the controllability and the observability Gramians of the error system. We then propose a gradient method that finds the (optimal) stable model, with fixed ℓ poles and k zeros.

关键词： Mathematical model Computational modeling Poles and zeros Linear systems Biological system modeling

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Data-driven leak localization in water distribution networks via dictionary learning and graph-based interpolation

arXiv

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arXiv 2021年

作者： Irofti, Paul Romero-Ben, Luis Stoican, Florin Puig, Vicenç Department of Computer Science Faculty of Mathematics and Computer Science University of Bucharest Romania Institut de Robòtica i Informàtica Industrial Universitat Politècnica de Catalunya Barcelona Spain Politehnica University of Bucharest Dept. of Automation Control and Systems Engineering Romania

In this paper, we propose a data-driven leak localization method for water distribution networks (WDNs) which combines two complementary approaches: graph-based interpolation and dictionary classification. The former estimates the complete WDN hydraulic state (i.e., hydraulic heads) from real measurements at certain nodes and the network graph. Then, these actual measurements, together with a subset of valuable estimated states, are used to feed and train the dictionary learning scheme. Thus, the meshing of these two methods is explored, showing that its performance is superior to either approach alone, even deriving different mechanisms to increase its resilience to classical problems (e.g., dimensionality, interpolation errors, etc.). The approach is validated using the L-TOWN benchmark proposed at BattLeDIM2020. Copyright © 2021, The Authors. All rights reserved.

关键词： Water distribution systems

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Dynamic Resilient Graph Games for State-Dependent Jamming Attacks Analysis on Multi-Agent systems

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IFAC-PapersOnLine 2020年第2期53卷 3421-3426页

作者： Yurid Nugraha Ahmet Cetinkaya Tomohisa Hayakawa Hideaki Ishii Quanyan Zhu Dept. of Systems and Control Engineering Tokyo Institute of Technology Tokyo 152-8552 Japan Information Systems Architecture Science Research Division National Institute of Informatics Tokyo 101-8430 Japan Dept. of Computer Science Tokyo Insitute of Technology Yokohama 226-8502 Japan Dept. of Electrical and Computer Engineering New York University Brooklyn NY 11201 USA

A cybersecurity problem for a multi-agent consensus problem is investigated through a dynamic game formulation. Specifically, we consider a game repeatedly played between a jamming attacker and a defender. The attacker attempts to jam the links between a number of agents to delay their consensus. On the other hand, the defender tries to maintain the connection between agents by attempting to recover some of the jammed links with the goal of achieving faster consensus. In each game, the players decide which links to attack/recover and for how long to continue doing so based on a Lyapunov-like function representing the largest difference between the states of the agents. We analyze the subgame perfect equilibrium of the game and obtain an upper bound of the consensus time that is influenced by the strategies of the players. The results are illustrated with a numerical example.

关键词： Multi-agent systems Consensus problem Game theory Cybersecurity

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V-Edge: Virtual edge computing as an enabler for novel microservices and cooperative computing

arXiv

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arXiv 2021年

作者： Dressler, Falko Chiasserini, Carla Fabiana Fitzek, Frank H.P. Karl, Holger Cigno, Renato Lo Capone, Antonio Casetti, Claudio Malandrino, Francesco Mancuso, Vincenzo Klingler, Florian Rizzo, Gianluca The School of Electrical Engineering and Computer Science TU Berlin Berlin Germany The Dept. of Electronics and Telecommunications Politecnico di Torino Torino Italy The School of Engineering Sciences as well as the Excellence Cluster CeTI TU Dresden Dresden Germany The Hasso-Plattner-Institute Potsdam Germany The Dept. of Information Engineering University of Brescia Brescia Italy The Dept. of Electronics Information and Bioengineering Politecnico di Milano Milano Italy The Dept. of Control and Computer Engineering Politecnico di Torino Torino Italy The Institute of Electronics Computer and Communication Engineering of the National Research Council of Italy Torino Italy IMDEA Networks Madrid Spain The Dept. of Computer Science Paderborn University Paderborn Germany The Research Institute of Information Systems HES-SO Valais-Wallis Switzerland University of Foggia Italy

As we move from 5G to 6G, edge computing is one of the concepts that needs revisiting. Its core idea is still intriguing: instead of sending all data and tasks from an end user's device to the cloud, possibly covering thousands of kilometers and introducing delays that are just owed to limited propagation speed, edge servers deployed in close proximity to the user, e.g., at some 5G gNB, serve as proxy for the cloud. Yet this promising idea is hampered by the limited availability of such edge servers. In this paper, we discuss a way forward, namely the virtual edge computing (V-Edge) concept. V-Edge bridges the gap between cloud, edge, and fog by virtualizing all available resources including the end users' devices and making these resources widely available using well-defined interfaces. V-Edge also acts as an enabler for novel microservices as well as cooperative computing solutions. We introduce the general V-Edge architecture and we characterize some of the key research challenges to overcome, in order to enable wide-spread and even more powerful edge services. Copyright © 2021, The Authors. All rights reserved.

关键词： Edge computing

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Mathematical Model of a Three-Phase Induction Motor with Asymmetrical Twelve-Zone Stator Windings

Mathematical Model of a Three-Phase Induction Motor with Asy...

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International Conference on Modern Electrical and Energy systems (MEES)

作者： Valerii Tytiuk Oleksii Chornyi Victor Busher Tatyana Siverskaya Mila Baranovskaya Vitalii Kuznetsov Department “Artificial Intelligence Technologies” NJSC “Karaganda Industrial University” Temirtau Kazakhstan Institute of Electromechanics Energy Saving and Automatic Control Systems Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine Dept. of Electrical Engineering and Electronics National University “Odessa Maritime Academy” Odessa Ukraine Department “Power Engineering” NJSC “Karaganda Industrial University” Temirtau Kazakhstan Department of Electromechanics Kryvyi Rih National University Kryvyi Rih Ukraine Department of the electrical engineering Ukrainian State University of Science and Technologies Dnipro Ukraine

ISBN: (纸本)9798350346848

The paper proposes a mathematical model of a three-phase induction motor with an asymmetrical twelve-zone winding of stator with parallel connection of subwindings. The mathematical model was developed using the theory of generalized electromechanical converter and contains equations of electrical equilibrium of six stator windings and three rotor windings. The equations for calculating the electromagnetic moment and the equations of motion of the induction motor with an asymmetrical twelve-zone stator winding rotor were obtained. The developed mathematical model in the form of cell-matrix equations has been implemented in MATLAB/Simulink.

关键词： Induction motors Torque Computational modeling Windings Stator windings Rotors Mathematical models

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Bayesian Neural Networks Uncertainty Quantification with Cubature Rules

Bayesian Neural Networks Uncertainty Quantification with Cub...

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International Joint Conference on Neural Networks (IJCNN)

作者： Peng Wang Nidhal C. Bouaynaya Lyudmila Mihaylova Jikai Wang Qibin Zhang Renke He Automatic Control & Systems Engineering Dept. The University of Sheffield Information and Navigation College Air Force Engineering University The 32nd Research Institute of CETC Department of Automation University of Science and Technology of China Department of Electrical and Computer Engineering Rowan University

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

Bayesian neural networks are powerful inference methods by accounting for randomness in the data and the network model. Uncertainty quantification at the output of neural networks is critical, especially for applications such as autonomous driving and hazardous weather forecasting. However, approaches for theoretical analysis of Bayesian neural networks remain limited. This paper makes a step forward towards mathematical quantification of uncertainty in neural network models and proposes a cubature-rule-based computationally-efficient uncertainty quantification approach that captures layer-wise uncertainties of Bayesian neural networks. The proposed approach approximates the first two moments of the posterior distribution of the parameters by propagating cubature points across the network nonlinearities. Simulation results show that the proposed approach can achieve more diverse layer-wise uncertainty quantification results of neural networks with a fast convergence rate.

关键词： Neural networks Uncertainty Bayes methods Computational modeling Gaussian distribution Two dimensional displays Weather forecasting

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On the Role of Models in Learning control: Actor-Critic Iterative Learning control

arXiv

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arXiv 2020年

作者： Poot, Maurice Portegies, Jim Oomen, Tom Control Systems Technology Group Dept. of Mechanical Engineering Eindhoven University of Technology Eindhoven Netherlands CASA Dept. of Mathematics and Computer Science Eindhoven University of Technology Eindhoven Netherlands

Learning from data of past tasks can substantially improve the accuracy of mechatronic systems. Often, for fast and safe learning a model of the system is required. The aim of this paper is to develop a model-free approach for fast and safe learning for mechatronic systems. The developed actor-critic iterative learning control (ACILC) framework uses a feedforward parameterization with basis functions. These basis functions encode implicit model knowledge and the actor-critic algorithm learns the feedforward parameters without explicitly using a model. Experimental results on a printer setup demonstrate that the developed ACILC framework is capable of achieving the same feedforward signal as preexisting model-based methods without using explicit model knowledge. Copyright © 2020, The Authors. All rights reserved.

关键词： Learning algorithms

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