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International Carpathian control Conference (ICCC)

作者： Stepan Ozana Filip Krupa Jakub Nemcik Gergely Takacs Jakub Mozaryn Petr Beremlijski Abhaya Singh Aleksandra Kawala-Sterniuk Department of Cybernetics and Biomedical Engineering VSB-Technical University of Ostrava Ostrava Czech Republic Institute of Automation Measurement and Applied Informatics Slovak University of Technology in Bratislava Bratislava Slovak Republic Institute of Automatic Control and Robotics Warsaw University of Technology Warsaw Poland Department of Applied Mathematics VSB-Technical University of Ostrava Ostrava Czech Republic Department of engineering University of Sannio Sannio Italy Department of Electrical Power and Renewable Energy Opole University of Technology Opole Poland

This paper deals with the design and implementation of adaptive nonlinear predictive control (NMPC). The resulting control system is deployed on a softPLC embedded target in real-time via the REXYGEN control system. The paper describes functional prototype using softPLC hosting the NMPC algorithm applied for a nonlinear system consisting of three coupled tanks. The NMPC algorithm is solved via the receding horizon control method (RHC), formulated as a nonlinear programming problem (NLP) and numerically computed using the SOLNP solver. The adaptivity is provided by online identification via moving horizon estimation (MHE), keeping the model updated to avoid a model-plant mismatch. The methodology described in this paper can be easily transferred to a wider group of industrial nonlinear processes. Such created control unit can run in a standalone mode or can be connected to some exiting control system providing a necessary computational power and thus upgrading the quality of control significantly.

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PoCET: a Polynomial Chaos Expansion Toolbox for Matlab

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IFAC-PapersOnLine 2020年第2期53卷 7256-7261页

作者： Felix Petzke Ali Mesbah Stefan Streif Automatic Control & System Dynamics Lab at Technische Universität Chemnitz Faculty for Electrical Engineering and Information Technology Chemnitz Germany Department of Chemical and Biomolecular Engineering University of California Berkeley CA USA

We introduce PoCET: a free and open-scource Polynomial Chaos Expansion Toolbox for Matlab, featuring the automatic generation of polynomial chaos expansion (PCE) for linear and nonlinear dynamic systems with time-invariant stochastic parameters or initial conditions, as well as several simulation tools. It offers a built-in handling of Gaussian, uniform, and beta probability density functions, projection and collocation-based calculation of PCE coefficients, and the calculation of stochastic moments from a PCE. Efficient algorithms for the calculation of the involved integrals have been designed in order to increase its applicability. PoCET comes with a variety of introductory and instructive examples. Throughout the paper we show how to perform a polynomial chaos expansion on a simple ordinary differential equation using PoCET, as well as how it can be used to solve the more complex task of optimal experimental design.

关键词： polynomial chaos simulation tools optimal experiment design optimal control

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Covariance estimation from compressive data partitions using a projected gradient-based algorithm

arXiv

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arXiv 2021年

作者： Monsalve, Jonathan Ramirez, Juan Esnaola, Iñaki Arguello, Henry Department of Electrical Engineering Universidad Industrial de Santander Bucaramanga680002 Colombia Department of Computer Science Universidad Rey Juan Carlos Madrid28933 Spain Department of Automatic Control and Systems Engineering The University of Sheffield Western Bank Sheffield United Kingdom Department Systems Engineering and Informatics Universidad Industrial de Santander Bucaramanga680002 Colombia

Covariance matrix estimation techniques require high acquisition costs that challenge the sampling systems’ storing and transmission capabilities. For this reason, various acquisition approaches have been developed to simultaneously sense and compress the relevant information of the signal using random projections. However, estimating the covariance matrix from the random projections is an ill-posed problem that requires further information about the data, such as sparsity, low rank, or stationary behavior. Furthermore, this approach fails using high compression ratios. Therefore, this paper proposes an algorithm based on the projected gradient method to recover a low-rank or Toeplitz approximation of the covariance matrix. The proposed algorithm divides the data into subsets projected onto different subspaces, assuming that each subset contains an approximation of the signal statistics, improving the inverse problem’s condition. The error induced by this assumption is analytically derived along with the convergence guarantees of the proposed method. Extensive simulations show that the proposed algorithm can effectively recover the covariance matrix of hyperspectral images with high compression ratios (8 − 15% approx) in noisy scenarios. Additionally, simulations and theoretical results show that filtering the gradient reduces the estimator’s error recovering up to twice the number of eigenvectors. © 2021, CC BY-NC-ND.

关键词： Covariance matrix

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Combining Trajectory Data with Analytical Lyapunov Functions for Improved Region of Attraction Estimation

arXiv

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arXiv 2021年

作者： Lugnani, Lucas Jones, Morgan Alberto, Luís F.C. Peet, Matthew Dotta, Daniel Faculty of Electrical and Computer Engineering University of Campinas Brazil The Department of Automatic Control and Systems Engineering University of Sheffield United Kingdom The São Carlos Engineering School University of São Paulo São Carlos Brazil The School for the Engineering of Matter Transport and Energy Arizona State University Tempe United States

The increasing uptake of inverter based resources (IBRs) has resulted in many new challenges for power system operators around the world. The high level of complexity of IBR generators makes accurate classical model-based stability analysis a difficult task. This paper proposes a novel methodology for solving the problem of estimating the Region of Attraction (ROA) of a nonlinear system by combining classical model based methods with modern data driven methods. Our method yields certifiable inner approximations of the ROA, typical to that of model based methods, but also harnesses trajectory data to yield an improved accurate ROA estimation. The method is carried out by using analytical Lyapunov functions, such as energy functions, in combination with data that is used to fit a converse Lyapunov function. Our methodology is independent of the function fitting method used. In this work, for implementation purposes, we use Bernstein polynomials to function fit. Several numerical examples of ROA estimation are provided, including the Single Machine Infinite Bus (SMIB) system, a three machine system and the Van-der-Pol system. Copyright © 2021, The Authors. All rights reserved.

关键词： Lyapunov functions

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Hidden attractors in a new fractional-order discrete system: Chaos, complexity, entropy, and control

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Chinese Physics B 2020年第5期29卷 174-181页

作者： Adel Ouannas Amina Aicha Khennaoui Shaher Momani Viet-Thanh Pham Reyad El-Khazali Laboratory of Mathematics Informatics and Systems(LAMIS)University of Laarbi TebessiTebessa12002Algeria College of Humanities and Sciences Ajman UniversityAjmanUAE Laboratory of Dynamical Systems and Control University of Larbi Ben M’hidiOum El BouaghiAlgeria Department of Mathematics Faculty of ScienceUniversity of JordanAmman 11942Jordan Nonlinear Systems and Applications Faculty of Electrical and Electronics EngineeringTon Duc Thang UniversityHo Chi Minh CityVietnam ECCE Department Khalifa UniversityAbu-Dhabi 127788United Arab Emirates

This paper studies the dynamics of a new fractional-order discrete system based on the Caputo-like difference *** is the first study to explore a three-dimensional fractional-order discrete chaotic system without *** phase portrait,bifurcation diagrams,and largest Lyapunov exponents,it is shown that the proposed fractional-order discrete system exhibits a range of different dynamical ***,different tests are used to confirm the existence of chaos,such as 0-1 test and C0 *** addition,the quantification of the level of chaos in the new fractional-order discrete system is measured by the approximate entropy ***,based on the fractional linearization method,a one-dimensional controller to stabilize the new system is *** results are presented to validate the findings of the paper.

关键词： discrete chaos discrete fractional calculus hidden attractor

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Assessment of Available Measurement Data, Data Breaks and Estimation of Missing Data from AMI Meters

Assessment of Available Measurement Data, Data Breaks and Es...

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International Symposium on Modern Electric Power Systems (MEPS)

作者： Barbara Kaszowska Andrzej Włóczyk Dariusz Zmarzły Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland

ISBN: (数字)9781728116419

ISBN: (纸本)9781728116426

Paper presents problems connected with collection, initial processing and validation of data from smart electric meters AMI installed in energy consumption points. Collected data should be then identified and classified. If the lack of data was detected they should be adequately estimated. Extreme disturbances in data sequences should be reduced too. The around-the-clock loads profiles are modelled on base of recorded and processed measurements. Verified profiles are used in estimation of missing data. The methods of modelling the around-the-clock loads profiles as well as the possibilities and methods of using the obtained models in estimation of missing data presented in the paper.

关键词： Meters Analytical models Power measurement Power demand Estimation Data models Load modeling

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Machine Learning and Computer Vision Techniques in Continuous Beehive Monitoring Applications: A Survey

arXiv

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arXiv 2022年

作者： Bilik, Simon Zemcik, Tomas Kratochvila, Lukas Ricanek, Dominik Richter, Miloslav Zambanini, Sebastian Horak, Karel Department of Control and Instrumentation Faculty of Electrical Engineering and Communication Brno University of Technology Technická 3058/10 Brno61600 Czech Republic Computer Vision and Pattern Recognition Laboratory Department of Computational Engineering Lappeenranta-Lahti University of Technology LUT Yliopistonkatu 34 Lappeenranta53850 Finland Computer Vision Lab Institute of Visual Computing & Human-Centered Technology Faculty of Informatics TU Wien Favoritenstr. 9/193-1 ViennaA-1040 Austria

Wide use and availability of machine learning and computer vision techniques allows development of relatively complex monitoring systems in many domains. Besides the traditional industrial domain, new applications appears also in biology and agriculture, where they may be used to detect infections, parasites and weeds, but also for automated monitoring and early warning systems. This goes in concordance with the introduction of the easily accessible hardware and development kits such as the Arduino, or RaspberryPi families. In this paper, we survey 50 papers focusing on the methods of automated beehive monitoring using computer vision techniques. Particularly on the pollen and Varroa mite detection together with the bee traffic monitoring. Such systems could also be used for monitoring of honeybee colonies and for the inspection of their health state, which could potentially identify dangerous states before the situation is critical, or to better plan periodic bee colony inspections and therefore save significant costs. Further on, we also include analysis of the research trends in this application field and we outline the possible directions of new development. Our paper is also aimed at veterinary and apidology professionals and experts, who may not be familiar with machine learning to introduce them to its capabilities, hence each family of techniques is prefaced by a brief theoretical introduction and motivation related to its base method. We hope that this paper will inspire other scientists to use machine learning techniques for other applications in beehive monitoring. © 2022, CC BY.

关键词： Computer vision

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Trajectory tracking of a tri-wheel mobile robot using the castor wheel's twist angle

Trajectory tracking of a tri-wheel mobile robot using the ca...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Ryszard Beniak Tomasz Pyka Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland

This paper presents an advanced control algorithm, which accounts for an additional impact of a castor wheel on a tri-wheel robot's trajectory. It demonstrates how to use the information on the angle of twist in order to limit the errors stemming from odometry. Thanks to applying the proven relationship between the trajectory's curvature and the angle of twist of a castor free wheel, we reduced the driving wheels' rotation errors in the robot's motion along the desired trajectory.

关键词： Wheels Mobile robots Trajectory Mathematical model Global Positioning System Numerical models

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Integration of Application Employed for Balance Difference Analysis with Network Asset Management and Measurement Data Management Systems in a Large Distribution Company

Integration of Application Employed for Balance Difference A...

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International Symposium on Modern Electric Power Systems (MEPS)

作者： Barbara Kaszowska Andrzej Włóczyk Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland

An application SORB is based on the statistical method of calculation of electric energy losses in distribution networks. The application Bi-sun has got new possibilities and functionalities last time which enable it&... 详细信息

ISBN: (数字)9781728116419

ISBN: (纸本)9781728116426

关键词： Energy loss Power measurement Area measurement Measurement uncertainty Loss measurement Time measurement Data models

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Unknown Input Based Observer Design for Wind Energy Conversion System with Time-Delay 5

Unknown Input Based Observer Design for Wind Energy Conversi...

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5th International Conference on Green Technology and Sustainable Development, GTSD 2020

作者： Vu, Van-Phong Wang, Wen-June Ngo, Van-Thuyen Truong, Dinh-Nhon Lee, Pei-Jun Do, Ton Duc Tong, Van-Ngoc Ho Chi Minh City University of Technology and Education Department of Automatic Control Ho Chi Minh City Viet Nam National Central University Department of Electrical Engineering Zhongli Taiwan National Chi-Nan University Department of Electrical Engineering Nantou Taiwan Nazarbayev University Department of Robotics and Mechatronics AstanaZ05H0P9 Kazakhstan Faculty of Electrical and Electronics Engineering Vietnam-Singapore Vocational College Binh Duong Viet Nam

ISBN: (纸本)9781728199825

A new approach to design a nonlinear observer for the Wind Energy Conversion System (WECSs) with the existence of a delay time state variable is proposed in this paper. The WECSs are modeled under a polynomial framework that allows us to apply the powerful methodology of the linear system to synthesize the observer. Unlike the previous paper, the delay time in this paper is arbitrary and unnecessary to satisfy the bound constraints or the time delay must be constant. Additionally, during operating the WECSs, the wind is taken into account the unknown disturbance that affects to the performance of WECSs. In this paper, the unknown input method is employed to design the observer which can eliminate the influences of the delay time parts and disturbance;as well as estimate the unknown states asymptotically. Based on the Lyapunov theory and Sum-Of-Square (SOS) technique, the conditions to synthesize the nonlinear observer are obtained in the main theorems. The simulation results are also provided to show the merit of the proposed method. © 2020 IEEE.

关键词： Linear systems

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