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arXiv 2022年

作者： Skirvin, Samuel J. Fedun, Viktor Silva, Suzana S.A. Van Doorsselaere, Tom Claes, Niels Goossens, Marcel Verth, Gary Centre for mathematical Plasma Astrophysics Mathematics Department KU Leuven Celestijnenlaan 200B bus 2400 LeuvenB-3001 Belgium Plasma Dynamics Group Department of Automatic Control & Systems Engineering The University of Sheffield SheffieldS3 7RH United Kingdom Plasma Dynamics Group Department of Mathematics and Statistics The University of Sheffield SheffieldS3 7RH United Kingdom

Magnetoacoustic waves in solar magnetic flux tubes may be affected by the presence of background rotational flows. Here, we investigate the behaviour of m = 0 and m = ±1 modes of a magnetic flux tube in the presence of linear background rotational flows embedded in a photospheric environment. We show that the inclusion of a background rotational flow is found to have little effect on the obtained eigensolutions for the axisymmetric m = 0 sausage mode. However, solutions for the kink mode are dependent on the location of the flow resonance modified by the slow frequency. A background rotational flow causes the modified flow resonances to possess faster phase speeds in the thin-tube (TT) limit for the case m = 1. This results in solutions for the slow body and slow surface kink modes to follow this trajectory, changing their dispersive behaviour. For a photospheric flux tube in the TT limit, we show that it becomes difficult to distinguish between the slow surface and fast surface kink (m = 1) modes upon comparison of their eigenfunctions. 2D velocity field plots demonstrate how these waves, in the presence of background rotational flows, may appear in observational data. For slow body kink modes, a swirling pattern can be seen in the total pressure perturbation. Furthermore, the tube boundary undergoes a helical motion from the breaking of azimuthal symmetry, where the m = 1 and m = −1 modes become out of phase, suggesting the resulting kink wave is circularly polarised. These results may have implications for seismology of magnetohydrodynamic waves in solar magnetic vortices. © 2022, CC BY.

关键词： Magnetohydrodynamics

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Artificial Neural Network-Based Direct Power control to Enhance the Performance of a Pmsg-Wind Energy Conversion System Under Real Wind Speed and Parameter Uncertainties: An Experimental Validation

SSRN

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SSRN 2023年

作者： Majout, Btissam Bossoufi, Badre Karim, Mohammed Skruch, Pawel Mobayen, Saleh El Mourabit, Youness El Zair Laggoun, Zakaria Laboratory of Engineering Modelling and Systems Analysis SMBA University Fez Morocco Department of Automatic Control and Robotics AGH University of Science and Technology Kraków30-059 Poland Graduate School of Intelligent Data Science National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou640301 Taiwan National School of Applied Sciences Abdelmalek Essaadi University Tetouan Morocco Laboratory of Electrotechnique Constantine Mentouri Brothers Constantine 1 University Constantine Algeria

With the increasing emphasis on embedding advanced technology into system controls, the Direct Power control (DPC) approach has garnered significant attention, owing to its straightforward and highly adaptable algorithm. It has been adopted in many applications. However, the variable frequency, harmonic distortion of the currents, and power ripples caused by Hysteresis controllers and switching tables decrease its effectiveness and robustness, affecting the system’s performance. For this reason, this paper proposed a new DPC based on Artificial Neural Network (ANN) approaches. In this approach, the hysteresis comparator and the switching table are substituted with ANN controllers and then applied on both sides: machine-side converter (MSC) and grid-side converter (GSC) of a Permanent Magnet Synchronous Generator based Wind Energy Conversion System (PMSG-WECS). Moreover, to make the system more efficient in varying wind conditions, this study expands the utilization of the artificial neural networks (ANN) to encompass the maximum power point tracking (MPPT) control strategy. To demonstrate the effectiveness of the proposed approach on the system behaviors, a simulation test was carried out in the Matlab/Simulink environment, using a real wind profile of a Moroccan city (Essaouira). In comparison to the classical DPC control, the simulation results showed the superior performance of the proposed ANN-DPC control in terms of reference tracking, response time, overshoot, precision, and its capacity to reduce the rate of power ripples and total harmonic distortion (THD) in the injected currents. Furthermore, a robustness test was also included in this work to check the robustness of the proposed control against parameters variation. In conclusion, the feasibility and effectiveness of the ANN-DPC control approach were confirmed through experimental validation using the dSPACE DS1104 board. © 2023, The Authors. All rights reserved.

关键词： MATLAB

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Minimization of constraint violation probability in model predictive control

arXiv

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arXiv 2020年

作者： Brüdigam, Tim Gaßmann, Victor Wollherr, Dirk Leibold, Marion The Department of Automatic Control Engineering The Technical University of Munich Germany The Department of Robotics Artificial Intelligence and Real-time Systems The Technical University of Munich Germany

While Robust Model Predictive control considers the worst-case system uncertainty, Stochastic Model Predictive control, using chance constraints, provides less conservative solutions by allowing a certain constraint violation probability depending on a predefined risk parameter. However, for safety-critical systems it is not only important to bound the constraint violation probability but to reduce this probability as much as possible. Therefore, an approach is necessary that minimizes the constraint violation probability while ensuring that the Model Predictive control optimization problem remains feasible. We propose a novel Model Predictive control scheme that yields a solution with minimal constraint violation probability for a norm constraint in an environment with uncertainty. After minimal constraint violation is guaranteed the solution is then also optimized with respect to other control objectives. Further, it is possible to account for changes over time of the support of the uncertainty. We first present a general method and then provide an approach for uncertainties with symmetric, unimodal probability density function. Recursive feasibility and convergence of the method are proved. A simulation example demonstrates the effectiveness of the proposed method. Copyright © 2020, The Authors. All rights reserved.

关键词： Robust control

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Kernel-based Regularized Iterative Learning control of Repetitive Linear Time-varying systems ⁎

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IFAC-PapersOnLine 2021年第7期54卷 738-743页

作者： Xian Yu Tianshi Chen Biqiang Mu Lennart Ljung School of Data Science The Chinese University of Hong Kong ShenZhen Guangdong 518172 P.R. China Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 P.R. China Division of Automatic Control Department of Electrical Engineering Linköping University Linköping SE-58183 Sweden

The selections for the model orders and the number of controller parameters have not been discussed for many data-driven iterative learning control (ILC) methods. If they are not chosen carefully, the estimated model and designed controller will lead to either large variance or large bias. In this paper we try to use the kernel-based regularization method (KRM) to handle the model estimation problem and the controller design problem for unknown repetitive linear time-varying systems. In particular, we have used the diagonal correlated kernel and the marginal likelihood maximization method for the two problems. Numerical simulation results show that smaller mean square errors for each time instant are obtained by using the proposed ILC method in comparison with an existing data-driven ILC approach.

关键词： Kernel-based regularization Iterative learning control Repetitive systems Linear time-varying systems

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Tutorial on Asymptotic Properties of Regularized Least Squares Estimator for Finite Impulse Response Model

arXiv

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arXiv 2021年

作者： Ju, Yue Chen, Tianshi Mu, Biqiang Ljung, Lennart The School of Data Science Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen518172 China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and System Science Chinese Academy of Sciences Beijing100190 China The Division of Automatic Control Department of Electrical Engineering Linköping University LinköpingSE-58183 Sweden

In this paper, we give a tutorial on asymptotic properties of the Least Square (LS) and Regularized Least Squares (RLS) estimators for the finite impulse response model with filtered white noise inputs. We provide three perspectives: the almost sure convergence, the convergence in distribution and the boundedness in probability. On one hand, these properties deepen our understanding of the LS and RLS estimators. On the other hand, we can use them as tools to investigate asymptotic properties of other estimators, such as various hyper-parameter estimators. © 2021, CC BY.

关键词： Probability distributions

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The method of teaching IT students computer analysis of ergonomic reserves of the effectiveness of automated control systems

The method of teaching IT students computer analysis of ergo...

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2020 International Conference on Sustainable Futures: Environmental, Technological, Social and Economic Matters, ICSF 2020

作者： Lavrov, Evgeniy Pasko, Nadiia Siryk, Olga Kisel, Natalia Sedova, Nelly Sumy State University Department of Computer Science Sumy Ukraine Sumy National Agrarian University Department of Cybernetics and Informatics Sumy Ukraine Taras Shevchenko National University of Kyiv Department of General Mathematics Kyiv Ukraine Southern Federal University Institute of Radio Engineering Systems and Control Taganrog Russia Maritime State University Named after G.I.Nevelskoy Department of Automatic and Information Systems Vladivostok Russia

In the article, we consider a technique for training university students, who study IT specialties to solve problems of finding ergonomic reserves to improve the efficiency of automated systems. We describe the structure of the "Ergonomics of Automated systems" course, software for evaluating and optimizing the activities of operators of "human-equipment-environment" systems, and methodological techniques for using ergonomic computer modeling to build effective automated control systems. Discipline is built using a mansystem approach to the study and design of automated systems, when a person is considered the main element of the system, but the diverse influence of hardware, software and information support, as well as the environment, is taken into account. A significant difference between the developed method and similar existing disciplines devoted to the study of the "human factor" is that, firstly, not only the characteristics of the human operator working with technology are studied, but also the mutual influence of system elements;secondly, the course is based on a qualimetric approach to assess the reliability of the activity and the economic results of this activity;thirdly, the computer modeling used is focused on optimization with the use of economic criteria of activity, while observing the requirements of ergonomic norms and standards. Functional networks developed by the scientific school "Efficiency, Reliability, and Quality of Ergotechnical systems" by Professor Anatoly Ilyich Gubinsky were used as a methodological basis for modeling and optimization of activities. © The Authors, published by EDP Sciences, 2020.

关键词： Ergonomics

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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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Bearing faults and broken bars simulation in an induction motor using an engineering tool 3

Bearing faults and broken bars simulation in an induction mo...

引用

3rd International Conference on Mechanical, Electric and Industrial engineering, MEIE 2020

作者： Caiza, Gustavo Garcia, Carlos Andres Blanque-Molina, Baldui Garcia, Marcelo Vladimir Department of Electronics Engineering Universidad Politecnica Salesiana Moran Valverde Av. Quito170146 Ecuador Faculty of Systems Electronics and Industrial Engineering Universidad Tecnica de Ambato De los Chasquis Av. Ambato180103 Ecuador Department of Electric Engineering Universitat Polit cnica de Catalunya Av. Victor Balaguer Vilanova i La geltru08800 Spain Department of Automatic Control and Systems University of the Basque Country Torres Quevedo Ingeniaria Plaza Bilbao48013 Spain

Industrial processes require reliable, safe, and continuous operation of electric motors. However, unexpected failures result in production losses, high emergency maintenance costs, damage to other related machines and prolonged shutdowns. Therefore, the development of failure analysis, detection and prevention systems is of high importance for the industrial sector. The following paper proposes the generation of a model of a squirrel cage induction motor in the software tool Simulink capable of simulating: i) broken bars and broken rotor rings, and ii) failures in the bearings of the motor, based on the Motor Current Signature Analysis (MCSA) technique which is a non-invasive method. Moreover, the Fast Fourier Transform (FFT) analysis is used to perform spectral investigation on the current to detect specific components that characterize faults in these conditions. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Simulink

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The energy revolution: Cyber physical advances and opportunities for smart local energy systems

arXiv

引用

arXiv 2021年

作者： Verba, Nandor Gaura, Elena McArthur, Stephen Konstantopoulos, George Wu, Jianzhoug Fan, Zhong Athanasiadis, Dimitrios Monasterios, Pablo Rodolfo Baldivieso Morris, Euan Hardy, Jeffrey Centre for Data Science Coventry University United Kingdom Department of Electronic and Electrical Engineering University of Strathclyde United Kingdom Department of Automatic Control & Systems Engineering University of Sheffield United Kingdom Department of Electrical and Electronic Engineering Cardiff University United Kingdom School of Computing and Mathematics Keele University United Kingdom Grantham Institute Imperial College London United Kingdom

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Coalitional predictive control: Consensus-based coalition forming with robust regulation

arXiv

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arXiv 2020年

作者： Baldivieso-Monasterios, Pablo R. Trodden, Paul A. Department of Automatic Control and Systems Engineering University of Sheffield Mappin Street SheffieldS1 3JD United Kingdom

This paper is concerned with the problem of controlling a system of constrained dynamic subsystems in a way that balances the performance degradation of decentralized control with the practical cost of centralized control. We propose a coalitional control scheme in which controllers of subsystems may, as the need arises, group together into coalitions and operate as a single entity. The scheme employs a robust form of distributed model predictive control for which recursive feasibility and stability are guaranteed, yet-uniquely-the reliance on robust invariant sets is merely implicit, thus enabling applicability to higher-order systems. The robust control algorithm is combined with an algorithm for coalition forming based on consensus theory and potential games;we establish conditions under which controllers reach a consensus on the sets of coalitions. The recursive feasibility and closed-loop stability of the overall time-varying coalitional control scheme are established under a sufficient dwell time, the existence of which is guaranteed. Copyright © 2020, The Authors. All rights reserved.

关键词： Model predictive control

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