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5th International Youth Scientific and Technical Conference Relay Protection and Automation, RPA 2022

作者： Kutumov, Yu. D. Shadrikova, T.Yu. Shuin, V.A. Ivanovo State Power Engineering University Jsc so Ups Branch of Ido Center Automatic Control of Electrical Power Systems Department Ivanovo Russia

ISBN: (数字)9798350399912

ISBN: (纸本)9798350399912

At the present time approximately 20% of 6-10 kV cable networks operate with resonant-grounded via arc-suppression coil (ASC) neutral point [1]. Meanwhile, an increasing number of experts note that resonant grounding of neutral point via ASC cannot solve the issue of single phase to earth faults (SPEF) negative consequences and their most dangerous variation, which is called intermittent arc single phase to earth fault (IASPEF) [for example, 2]. The main reasons for the inadequate efficiency of this neutral grounding mode are higher harmonic components in steady-state SPEF current, as well as higher harmonic components which are due to intensive transient processes during SPEF, which cannot be compensates by the usage of ASC. For the compensation of these components it is necessary to apply the devices, which will be complement ASC;these devices, together with the ASC, can be called a system of full compensation of the SPEF current. © 2022 IEEE.

关键词： Electric grounding

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A Predictive control based Scheme for Maximum Power Extraction of PMSG based Wind Turbine systems

A Predictive Control based Scheme for Maximum Power Extracti...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Fahimeh Shiravani Jose Antonio Cortajarena Patxi Alkorta Mikel Gonzalez Perez Oscar Barambones Department of Automatic Control and Systems Engineering School of Engineering of Gipuzkoa – EIG/Eibar Basque Country University Spain Department of Electronic Technology School of Engineering of Gipuzko– EIG/Eibar Basque Country University Spain Department of Automatic Control and Systems Engineering School of Engineering of Gipuzkoa-EIG/Eibar Basque Country University Spain Department of Automatic Control and Systems Engineering School of Engineering of Vitoria Basque Country University Spain

In this proposal, a predictive control scheme is considered for PMSG based wind turbine system in order to maximize power extraction. The main goal is to maintain the turbine tip-speed ratio (and consequently the power coefficient) at its optimal point and regulate the PMSG rotor speed in reaction to the variation of wind speed. The control of generator speed is done by employing a generalized predictive controller. This regulator by taking advantage of the predictive feature can prepare the generator to react to the upcoming wind in advance and consequently increases the efficiency of the turbine. Also, it has been demonstrated that this controller enhances the transient response of the system compared to the conventional methods. The proposed controller has been validated through Matlab/Simulink and an experimental test bench.

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A Regularized LSTM Method for Predicting Remaining Useful Life of Rolling Bearings

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International Journal of Automation and computing 2021年第4期18卷 581-593页

作者： Zhao-Hua Liu Xu-Dong Meng Hua-Liang Wei Liang Chen Bi-Liang Lu Zhen-Heng Wang Lei Chen School of Information and Electrical Engineering Hunan University of Science and TechnologyXiangtan 411201China Department of Automatic Control and Systems Engineering University of SheffieldSheffield SI 3JDUK

Rotating machinery is important to industrial production. Any failure of rotating machinery, especially the failure of rolling bearings, can lead to equipment shutdown and even more serious incidents. Therefore, accurate residual life prediction plays a crucial role in guaranteeing machine operation safety and reliability and reducing maintenance cost. In order to increase the forecasting precision of the remaining useful life(RUL) of the rolling bearing, an advanced approach combining elastic net with long short-time memory network(LSTM) is proposed, and the new approach is referred to as E-LSTM. The E-LSTM algorithm consists of an elastic mesh and LSTM, taking temporal-spatial correlation into consideration to forecast the RUL through the LSTM. To solve the over-fitting problem of the LSTM neural network during the training process, the elastic net based regularization term is introduced to the LSTM *** this way, the change of the output can be well characterized to express the bearing degradation mode. Experimental results from the real-world data demonstrate that the proposed E-LSTM method can obtain higher stability and relevant values that are useful for the RUL forecasting of bearing. Furthermore, these results also indicate that E-LSTM can achieve better performance.

关键词： Deep learning fault diagnosis fault prognosis long and short time memory network(LSTM) rolling bearing rotating machinery regularization remaining useful life prediction(RUL) recurrent neural network(RNN)

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Physics-Informed Neural Networks for Learning the Parameters of Commercial Adaptive Cruise control systems

Physics-Informed Neural Networks for Learning the Parameters...

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IEEE Conference on Decision and control

作者： Theocharis Apostolakis Konstantinos Ampountolas Department of Mechanical Engineering Automatic Control and Autonomous Systems Laboratory University of Thessaly Volos Greece

This paper develops a physics-informed neural network (PINN) for learning the parameters of commercially implemented adaptive cruise control (ACC) systems. The constant time-headway policy (CTHP) is adopted to emulate the core functionality of stock ACC systems (proprietary control logic and its parameters) which is not publicly available. Multi-layer artificial neural networks is a class of universal approximators, and thus the developed PINN can serve as a surrogate approximator to capture the longitudinal dynamics of ACC-engaged vehicles and efficiently learn the unknown parameters of the CTHP. The ability of the PINN to infer the unknown ACC parameters is tested on both synthetic and empirical data of space-gap and relative velocity involved ACC-engaged vehicles in platoon formation. The results have demonstrated the superior predictive ability of the proposed PINN to learn the unknown design parameters of stock ACC systems of different vehicle makes. The set of ACC model parameters obtained from the PINN revealed that the stock ACC system of the considered vehicles in three experimental campaigns is neither $\mathcal{L}_systems$ nor $\mathcal{L}_{\infty}$ string stable.

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Dynamic Optimization of Electric Vehicle Charging for Sustainable Power Grids using Sine Hunter-Prey Optimization with GRUs 3

Dynamic Optimization of Electric Vehicle Charging for Sustai...

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3rd IEEE International Conference on Electrical Power and Energy systems, ICEPES 2024

作者： Syed, Mohd Khizar Chandra Behera, Prakash Josephson, P Joel Khan, Shamim Ahmad Kholmukhamedov, Timur Ponni Valavan, M. Kohinoor college Department of Physics Maharashtra India St. Claret College Department of Science Bangalore India Malla Reddy Engineering College Department of ECE Telangana Medchal Malkajgiri India Glocal School of Science & Technology Glocal University Uttar Pradesh India Turin Polytechnic University Automatic Control and Computer Engineering Department Tashkent Uzbekistan K.Ramakrishnan College of Engineering Department of AI & DS Tamil Nadu Trichy India

ISBN: (纸本)9798350390728

The integration of electric vehicles (EVs) into power grids presents a significant challenge for sustainability due to their dynamic charging demands and the need to accommodate renewable energy sources. Existing optimization methods often fail to adequately address the complexity of this problem. In this study, propose a novel approach that combines Sine Hunter-Prey Optimization (SHPO) with Gated Recurrent Units (GRUs) to dynamically optimize EV charging for sustainable power grid operation. Traditional optimization methods struggle to capture the nonlinear and time-varying nature of EV charging demands and renewable energy availability. To overcome this limitation, SHPO's ability to efficiently explore complex solution spaces and GRUs' capability to model temporal dependencies in sequential data. This proposed method optimizes EV charging schedules by considering grid stability, renewable energy utilization, and cost minimization. Validating the approach using historical data on EV charging patterns, renewable energy generation, and grid conditions. Performance metrics include grid stability indices, renewable energy integration rates, and cost savings compared to baseline strategies. Experimental results demonstrate that the method outperforms traditional optimization techniques, leading to more sustainable and resilient power grid operation with 92% stability. Overall, this study contributes to advancing the modern methods in dynamic optimization of EV charging, paving the way for more sustainable transportation and energy systems. © 2024 IEEE.

关键词： State of charge

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Real-time Pricing Mechanism for V2G Using Distributed Bilevel Optimization 63

Real-time Pricing Mechanism for V2G Using Distributed Bileve...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： You, Jiawei Dai, Xinliang Jiang, Yuning Yin, Haoyu Shi, Yuanming Jones, Colin N. ShanghaiTech University School of Information Science and Technology China Epfl Switzerland Karlsruhe Institute of Technology Institute for Automation and Applied Informatics Germany Epfl Automatic Control Laboratory Switzerland Washington University in St. Louis Department of Electrical and Systems Engineering United States

ISBN: (纸本)9798350316339

This paper explores the impact of the burgeoning electric vehicle (EV) presence on distribution grid operations, highlighting the challenges they present to conventional pricing strategies due to their dual role as power consumers and suppliers, coupled with their energy storage capabilities. We propose an advanced real-time pricing model for the electricity market, employing a novel distributed bilevel optimization framework. This framework distinguishes between the distribution system operator (DSO) at the upper level and the EVs at the lower level, each aiming to optimize profit margins. The optimization includes power flow constraints at the upper level to ensure efficient operation within safe system limits, while model predictive control (MPC) is used to optimize lower-level EV responses. Additionally, we provide a rigorous convergence analysis of the proposed bilevel optimization method. Detailed convergence studies and simulation results demonstrate the effectiveness and superiority of the proposed algorithm. © 2024 IEEE.

关键词： Predictive control systems

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Digital framework for metallic subtractive process planning: Liger optimisation case study 57

Digital framework for metallic subtractive process planning:...

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18th IFAC Workshop on Time Delay systems, TDS 2024

作者： Duro, João A. Ward, Rob Rooke, Jack Pickford, Emily Bonnell, Rich Brown, Adam Purshouse, Robin C. Curtis, David Department of Automatic Control and Systems Engineering University of Sheffield SheffieldS1 3JD United Kingdom University of Sheffield Advanced Manufacturing Research Centre University of Sheffield RotherhamS60 5TZ United Kingdom

Metallic subtractive process planning is challenging. It requires a blend of expert knowledge, experience, and established manufacturing methods. Decision-making in this domain is multifaceted and complex, and this includes the need to satisfy multiple conflicting demands faced by the manufacturing sector today. However, with the evolving landscape of manufacturing, combined with increased adoptions of digital technologies, the traditional rules of thumb are becoming obsolete. In response, this research investigated these decision-making processes within a subset of the digital framework for subtractive process planning. In particular, it has demonstrated that an advanced open-source optimisation tool (Liger) could be integrated with commercial industrial software and applied to a machining case study. The integrated software intelligently executed and automated simulations using advanced optimisation techniques. The outputs are a range of optimised solutions that support manufacturing engineers' decision-making. One of the major benefits of the open-source software is that it provides an intuitive to use interface suitable for the non-expert in optimisation, offers a varied range of state-of-the-art multi-objective optimisation algorithms, and is capable of incorporating many different third-party types of software, models and simulations. In this paper, the Liger software has been applied to a simple case study to find the best feedrate and depths of cut that simultaneously minimise the cutting force and the time it takes to complete the machining process. The case study demonstrates proof-of-principle results that the optimisation software can be implemented in a wider process planning context with additional digital manufacturing simulation models. © 2024 The Authors.

关键词： Process planning

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Automation 5.0: The Key to systems Intelligence and Industry 5.0

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IEEE/CAA Journal of automatica Sinica 2024年第8期11卷 1723-1727页

作者： Ljubo Vlacic Hailong Huang Mariagrazia Dotoli Yutong Wang Petros A.Ioannou Lili Fan Xingxia Wang Raffaele Carli Chen Lv Lingxi Li Xiaoxiang Na Qing-Long Han Fei-Yue Wang Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith UniversityNathanQLD 4111Australia Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic UniversityHong KongChina Department of Electrical and Information Engineering Polytechnic of Bari70126 BariItaly State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190and also with the Qingdao Academy of Intelligent IndustriesQingdao 266114China Department of Electrical Engineering-Systems University of Southern CaliforniaLos AngelesCA 90007 USA School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 Beijing Huairou Academy of Parallel Sensing Beijing 101499China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University IndianapolisIndianapolisIN 46202 USA Department of Engineering University of CambridgeCB21TN CambridgeU.K. School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Dazhou Artificial Intelligence Institute Dazhouand the Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

AUTOMATION has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with *** rise of steam engines and water wheels represented the first generation of industry,which is now called Industry Citation:***,***,***,***,***,***,***,***,***,***,***,Q.-***,and F.-***,“Automation 5.0:The key to systems intelligence and Industry 5.0,”IEEE/CAA ***,vol.11,no.8,pp.1723-1727,Aug.2024.

关键词： Automation machinery intelligence

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Steps Toward Industry 5.0:Building“6S”Parallel Industries With Cyber-Physical-Social Intelligence

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IEEE/CAA Journal of automatica Sinica 2023年第8期10卷 1692-1703页

作者： Xingxia Wang Jing Yang Yutong Wang Qinghai Miao Fei-Yue Wang Aijun Zhao Jian-Ling Deng Lingxi Li Xiaoxiang Na Ljubo Vlacic School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE Macao University of Science and Technology Macao 999078China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of SciencesBeijing 100098 State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China North Automatic Control Technology Institute Taiyuan 030006China China Huaneng Group Co. Ltd.Beijing 100031China Department of Electrical and Computer Engineering Indiana University-Purdue University Indianapolis(IUPUI)IndianapolisIN 46202 USA Department of Engineering University of CambridgeCambridgeCB21PZUK School of Engineering and Built Environment Griffith UniversityGold CoastQLD 4222Australia

Very recently,intensive discussions and studies on Industry 5.0 have sprung up and caused the attention of researchers,entrepreneurs,and policymakers from various sectors around the ***,there is no consensus on why and what is Industry 5.0 *** this paper,we define Industry 5.0from its philosophical and historical origin and evolution,emphasize its new thinking on virtual-real duality and human-machine interaction,and introduce its new theory and technology based on parallel intelligence(PI),artificial societies,computational experiments,and parallel execution(the ACP method),and cyber-physical-social systems(CPSS).Case studies and applications of Industry 5.0 over the last decade have been briefly summarized and analyzed with suggestions for its future *** believe that Industry 5.0 of virtual-real interactive parallel industries has great potentials and is critical for building smart *** are outlined to ensure a roadmap that would lead to a smooth transition from CPS-based Industry 4.0 to CPSS-based Industry 5.0 for a better world which is Safe in physical spaces,S ecure in cyberspaces,Sustainable in ecology,Sensitive in individual privacy and rights,Service for all,and Smartness of all.

关键词： ACP artificial intelligence CPS CPSS Industry 4.0 Industry 5.0 parallel industries parallel intelligence

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Detecting Changes in Functional State: A Comparative Analysis Using Wearable Sensors and a Sensorized Tip

Detecting Changes in Functional State: A Comparative Analysi...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Janire Otamendi Asier Zubizarreta Department of Automatic Control and Systems Engineering Faculty of Engineering University of the Basque Country UPV/EHU Bilbao Spain

Gait analysis can provide relevant information about the physical and neurological conditions of individuals. For this reason, several studies have recently been carried out in an attempt to monitor people's gait and automatically detect gait anomalies. Among the various monitoring systems available for gait analysis, wearable sensors are considered the gold standard due to their wide capture range and low cost. However, in the case of people that require assistive devices for walking, some studies have proposed the use of sensorized devices in order to minimize invasiveness. Nevertheless, there is still a lack of comparative works that evaluate the performance of sensorized assistive devices for walking with widely used wearable sensors. Hence, this paper presents a comparison between the performance of accelerometer-based wearable sensors and a sensorized tip developed by the authors to detect gait anomalies. The comparative study has been carried out in a controlled environment with five healthy subjects, in which three different physical states have been simulated. A machine-learning based anomaly detection approach has been implemented based on the data captured by a set of wearable sensors and the sensorized tip, and the overall performance of both monitoring systems has been evaluated. Results show that even if both devices can provide an average accuracy of more than 80% in gait anomaly detection, the sensorized tip provides better performance.

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