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IEEE NW Russia Young Researchers in Electrical and Electronic engineering Conference (EIConRusNW)

作者： Nguyen Viet Phuong Nguyen Trong Tuyen Nguyen Duy Khanh Nguyen Ngoc Hung Department of Aerospace Control Systems Academy of Military Science and Technology Hanoi Vietnam Department of Biomedical Engineering Le Quy Don Technical University Hanoi Vietnam Department of Automatic Control Systems Saint Petersburg State Electrotechnical University Hanoi Vietnam Department of Aerospace Control Systems Le Quy Don Technical University Hanoi Vietnam

Two-axis gimbals are used in stabilizing and controlling the aiming of optical systems. The main task is to isolate the angular motion of the payload and the disturbances affecting the optical axis of the camera while maintaining the camera’s orientation locked onto the target. Currently, two commonly used gimbal structures are the Yaw-Pitch type and the Roll-Swing type. In this paper, we delve into an in-depth study to develop the full mathematical models for both types, thereby analyzing and evaluating the influence of the cross-channel noise moment effects caused by gimbal imbalance on the stability and aiming control quality under complex angular motion conditions of the payload. Simulation results conducted using MATLAB/SIMULINK with the two-axis gimbal model demonstrate that employing a robust control system significantly reduces the impact of disturbances and enhances the quality of control and stability of the transmission system.

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Machine Learning-based OWC Diagnosis Using Real Measured Data from Wave Power Plants

Machine Learning-based OWC Diagnosis Using Real Measured Dat...

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IEEE PES Asia-Pacific Power and Energy engineering Conference (APPEEC)

作者： Fares M’Zoughi Jon Lekube Izaskun Garrido Aitor J. Garrido Automatic Control Group - ACG Department of Automatic Control and Systems Engineering Faculty of Engineering of Bilbao - EIB/BIE University of the Basque Country - UPV/EHU Bilbao Spain Biscay Marine Energy Platform BiMEP Armintza Spain

ISBN: (数字)9798350318098

ISBN: (纸本)9798350318104

The present manuscript introduces a classification for power take-off (PTO) diagnosis in Wave Energy Converter (WEC) farms. The suggested strategy has been tested on the Mutriku Multiple Oscillating Water Column-based wave power plant in order to reduce the Levelized Cost of Energy (LCoE) by implementing predictive maintenance strategies. This has been achieved by employing Linear Discriminant Analysis (LDA) to determine the furthermost relevant features from the measured data. Then the Support Vector Machine (SVM) has been implemented as a classification technique to classify the state of the OWC system.

关键词： Support vector machines Vibrations Training Power measurement Wave power Biological system modeling Predictive models

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Fractional order MRAC control design for a lightning system based on a fractional order second degree model

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IFAC-PapersOnLine 2024年第12期58卷 95-100页

作者： Samir Ladaci Seif Eddine Khelas Amani R Ynineb Dana Copot Clara-Mihaela Ionescu Ecole Nationale Polytechnique Depart. Automatic Control Eng. El Harrach 16200 Algiers Algeria National Polytechnic School of Constantine E.E.A. Department 25100 Constantine Algeria Research Group on Dynamical Systems and Control Department of Electromechanical Systems and Metal Engineering Ghent University B-9052 Ghent Belgium

This paper presents a new adaptive fractional-order MRAC controller design for the class of non-integer second-order systems. The update of the control law gains follows a derivative of fractional order equal to the order of the controlled system model. The stability analysis of the control system has been performed based on Lyapunov theorem. We apply this control law to an experimental multivariable lightning system. The results obtained show the efficiency and performance improvement of the proposed control solution compared to the classical MRAC.

关键词： Fractional order system adaptive control MRAC FOMRAC Lightning system

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An Integrated Observer Framework Based Mechanical Parameters Identification for Adaptive control of Permanent Magnet Synchronous Motor

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Complex System Modeling and Simulation 2022年第4期2卷 354-367页

作者： Zhong Liao Zhaohua Liu Lei Chen Mingyang Lyu Dian Wang Faming Wu Zhengheng Wang Hualiang Wei the School of Information and Electrical Engineering Hunan University of Science and TechnologyXiangtan 411201China the Wind Power Business Division CRRC Zhuzhou Institute Co.Ltd.Zhuzhou 412001China. the Department of Automatic Control and Systems Engineering University of SheffieldSheffieldS13JDUK.

An integrated observer framework based mechanical parameters identification approach for adaptive control of permanent magnet synchronous motors is proposed in this ***,an integrated observer framework is established for mechanical parameters’estimation,which consists of an extended sliding mode observer(ESMO)and a Luenberger *** at minimizing the influence of parameters coupling,the viscous friction and the moment of inertia are obtained by ESMO and the load torque is identified by Luenberger observer *** obtaining estimates of the mechanical parameters,the optimal proportional integral(PI)parameters of the speed-loop are determined according to third-order best design *** a result,the controller can adjust the PI parameters in real time according to the parameter changes to realize the adaptive control of the ***,the disturbance is compensated according to the ***,the experiments were carried out on simulation platform,and the experimental results validated the reliability of parameter identification and the efficiency of the adaptive control strategy presented in this paper.

关键词： parameter identification permanent magnet synchronous motor adaptive control extended sliding mode observer Luenberger observer

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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

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Energy Reports 2024年 11卷 4356-4378页

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 Krakow 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 considerable attention due to its simple and highly adaptable algorithm. This approach has been increasingly recognized in numerous 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. © 2024 The Authors

关键词： MATLAB

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A study on preterm birth predictions using physiological signals,medical health record information and low-dimensional embedding methods

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IET Cyber-systems and Robotics 2021年第3期3卷 228-244页

作者： Ejay Nsugbe Oluwarotimi William Samuel Ibrahim Sanusi Mojisola Grace Asogbon Guanglin Li Nsugbe Research Labs SwindonUK Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences ShenzhenChina Department of Automatic Control and Systems Engineering The University of SheffieldSheffieldUK

Preterm births have been seen to have psychological and financial implications;current surveys suggest that amongst the various methods of preterm prediction,there is yet to exist a reliable and standard means of predicting preterm *** study investigates the application of electrohysterogram and tocogram signals acquired at various points during the third pregnancy trimester,alongside information from the patients'medical health record regarding the pregnancy,towards preterm prediction and an associated delivery imminency *** addition to this,the impact of both linear and non-linear dimensional embedding methods towards the preterm prediction is *** classification exercises were carried out using a support vector machine and decision tree,both of which have a certain degree of model interpretability and have potential to be introduced into a clinical operating framework.

关键词： cybernetics decision-making decision-tree classifier machine intelligence machine learning sensor fusion

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The Fundamental Limitations of Learning Linear-Quadratic Regulators

arXiv

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arXiv 2023年

作者： Lee, Bruce D. Ziemann, Ingvar Tsiamis, Anastasios Sandberg, Henrik Matni, Nikolai Department of Electrical and Systems Engineering University of Pennsylvania United States Automatic Control Laboratory ETH Zurich Switzerland Division of Decision and Control Systems KTH Royal Institute of Technology Sweden

We present a local minimax lower bound on the excess cost of designing a linear-quadratic controller from offline data. The bound is valid for any offline exploration policy that consists of a stabilizing controller and an energy bounded exploratory input. The derivation leverages a relaxation of the minimax estimation problem to Bayesian estimation, and an application of Van Trees’ inequality. We show that the bound aligns with system-theoretic intuition. In particular, we demonstrate that the lower bound increases when the optimal control objective value increases. We also show that the lower bound increases when the system is poorly excitable, as characterized by the spectrum of the controllability gramian of the system mapping the noise to the state and the H∞ norm of the system mapping the input to the state. We further show that for some classes of systems, the lower bound may be exponential in the state dimension, demonstrating exponential sample complexity for learning the linear-quadratic regulator offline. © 2023, CC BY.

关键词： Bayesian networks

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Enhancing Motion Prediction by a Cooperative Framework

Enhancing Motion Prediction by a Cooperative Framework

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IEEE Symposium on Intelligent Vehicle

作者： Javier Araluce Alberto Justo Asier Arizala Leonardo González Sergio Díaz TECNALIA Basque Research and Technology Alliance (BRTA) Derio Spain Department of Automatic Control and Systems Engineering University of the Basque Country (UPV/EHU) Bilbao Spain

ISBN: (数字)9798350348811

ISBN: (纸本)9798350348828

Cooperative perception is a technique that enhances the on-board sensing and perception of automated vehicles by fusing data from multiple sources, such as other vehicles, roadside infrastructure, cloud/edge servers, among others. It can improve the performance of automated driving in complex scenarios, like unsignalled roundabouts or intersections where the visibility and awareness of other road users are limited. Motion Prediction (MP) is a key component of cooperative perception, as it enables the estimation and prediction of microscopic traffic states, such as the positions and speeds of all vehicles. It relies on information from other agents and their relationships among them, so the information provided by external sources is valuable because it enhances the understanding of the *** this paper, we present improved MP through Vehicle to Vehicle (V2V) communication. We have trained Hierarchical Vector Transformer (HiVT) to be a map-less solution that can be used in road domains. With this model, we have implemented and compared two association methods to evaluate our framework on a real V2V dataset (V2V4Real). Our evaluation concludes that our V2V MP improves performance due to better scene understanding over a single-vehicle MP.

关键词： Intelligent vehicles Roads Microscopy Vehicular ad hoc networks Estimation Transformers Vectors

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Mitigating Undesirable Oscillatory Behavior in Barge-type Floating Offshore Wind Turbines through Oscillating Water Columns

Mitigating Undesirable Oscillatory Behavior in Barge-type Fl...

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IEEE PES Asia-Pacific Power and Energy engineering Conference (APPEEC)

作者： Payam Aboutalebi Dong Trong Nguyen Aitor J. Garrido Izaskun Garrido Department of Automatic Control and Systems Engineering Engineering School of Bilbao - EIB/BIE Automatic Control Group - ACG University of the Basque Country - UPV/EHU Bilbao Spain Department of Marine Technology Norwegian University of Science and Technology (NTNU) Trondheim Norway

ISBN: (数字)9798350318098

ISBN: (纸本)9798350318104

This paper addresses the challenge of reducing undesired oscillations in barge-type floating wind turbines (FWTs) caused by wind and wave forces, which result in fluctuations in generator power and system oscillations. These oscillations can negatively impact the system’s lifespan, power generation, maintenance costs, and component stress. To mitigate these issues, oscillating water columns (OWCs) are integrated within the FWT substructure. A control strategy is proposed for the OWCs based on response amplitude operators, aiming to minimize oscillations in a 5 MW wind turbine structure. A considered case study is conducted for above-rated wind speeds to evaluate the effectiveness of the controllers and to compare the performance of an uncontrolled FWT against a controlled FWT integrated with OWCs. The findings demonstrate the efficacy of the control strategy in pitch oscillations reducing for 29.9% and generated power fluctuations reducing for 23.03% and highlight the advantages of integrating OWCs in floating offshore wind turbines.

关键词： Vibrations Fluctuations Wind speed Switches Wind power generation Valves control systems

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Data-driven modeling of heat pumps and thermal storage units for MPC

Data-driven modeling of heat pumps and thermal storage units...

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2023 International Conference on the Built Environment in Transition, CISBAT 2023

作者： Brandes, M. Cai, H. Vivian, J. Croci, L. Heer, P. Smith, R. Urban Energy Systems Laboratory Empa Dübendorf Switzerland Dept. of Industrial Engineering University of Padova Padua Italy Dept. of Power System Development Ricerca Sistema Energetico SpA Milan Italy Automatic Control Laboratory Department of Electrical Engineering and Information Technology ETH Zurich Switzerland

Heat pumps can play a crucial role in the European energy strategy 2050, which aims to achieve net-zero greenhouse gas emissions. When coupled with thermal energy storage and integrated with advanced control strategies, heat pump operation can be optimized to reduce carbon footprint and respond to the needs of system operators. However, to scale in a multitude of buildings, the transferability of the modeling into heterogeneous systems is crucial. In this paper, two different interpretable linear models, a hybrid (grey-box) and a fully data-driven (black-box) model are investigated. Specifically, two regression-based identification methods (SINDYc and DMDc) are used for dynamic models and the LASSO regression is used for static models. The transferability of the approach is evaluated using two real-world facilities with heterogeneous sizing and configuration. The results show a similar simulation performance for both cases with a maximum normalized RMSE of 0.41 and 0.60, respectively. This confirms the transferability of the approach that is necessary for large-scale implementation. © 2023 Institute of Physics Publishing. All rights reserved.

关键词： Carbon footprint

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