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

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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Upgrading and testing of the UPV/EHU Stellarator 13

Upgrading and testing of the UPV/EHU Stellarator

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13th International Conference on Information, Intelligence, systems and Applications, IISA 2022

作者： Garrido, Aitor J. Marco, Aitor De La Sen, Manuel Oleagordia, Inigo Garrido, Izaskun University of the Basque Country - UPV/EHU Automatic Control Group - Acg Institute of Research and Development of Processes - Iidp Department of Automatic Control and Systems Engineering Faculty of Engineering of Bilbao Po Rafael Moreno 3 Bilbao48013 Spain University of the Basque Country - UPV/EHU. Automatic Control Group - Ac Advanced Design and Analysis Department Idom Zarandoa Etorb. 23 Bilbao48015 Spain University of the Basque Country - UPV/EHU Automatic Control Group - Acg Institute of Research and Development of Processes - Iidp Department of Electricity and Electronics Faculty of Science and Technology B° Sarriena s/n Leioa48080 Spain

ISBN: (数字)9781665463904

ISBN: (纸本)9781665463904

This paper deals with the upgrade and testing of the of the Ultra-Low Iota Super Elongated Stellarator of the University of the Basque Country. The main upgrades affect to the coil system but also to the microwave source and the data acquisition system. Therefore, it is necessary to update its State-Space model. The updated model is validated by means of experimental output data showing an accurate matching with the real system. Then, in order to test the new model, a Model Predictive control-MPC scheme is successfully implemented both in simulation and experimentally using a real-time control platform. © 2022 IEEE.

关键词： Model predictive control

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A Machine-Learning Approach for the Development of a FOWT Model Integrated with Four OWCs

A Machine-Learning Approach for the Development of a FOWT Mo...

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Circuits, systems, Communications and Computers (CSCC), International Conference on

作者： Irfan Ahmad Fares Mzoughi Payam Aboutalebi Izaskun Garrido Aitor Garrido Automatic Control Group-ACG Department of Automatic Control and Systems Engineering University of the Basque Country UPV/EHU Bilbao Spain

ISBN: (纸本)9781665481878

The wind-wave excitations cause structural vibrations on the Floating Offshore Wind Turbines (FOWT) pressing the power generation efficiency and reducing the life expectancy. In particular, tower-top displacement and barge-type platform pitch dynamics are extremely sensitive to wind speed and wave elevation to the point that may even lead to structural instability in extreme conditions. Having into account that computational techniques such as Artificial Neural Networks (ANNs) are widely used in artificial intelligence because of their strong predicting and forecasting capabilities, the aim of this article is to create a deep-layer ANN model that incorporates Oscillating Water Columns (OWCs) into the barge platform. This ANN model enables to address stability issues of the hybrid floating offshore wind platform. The proposed control-oriented model has been successfully validated to achieve adequate dynamic behavior and structural performance using FAST.

关键词： Vibrations Computational modeling Wind speed Artificial neural networks Machine learning Predictive models Aerodynamics

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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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Vibration Mitigation of Hybrid Oscillating Water Column-Floating Offshore Wind Turbine Using ANFIS-Based Airflow control 16th

Vibration Mitigation of Hybrid Oscillating Water Column-Floa...

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16th APCA International Conference on automatic control and Soft Computing, controlO 2024

作者： M’zoughi, Fares Aboutalebi, Payam Ahmad, Irfan Rouch, Tahereh Bagheri Garrido, Izaskun Garrido, Aitor J. De La Sen, Manuel Automatic Control Group—ACG Institute of Research and Development of Processes—IIDP Department of Automatic Control and Systems Engineering Faculty of Engineering of Bilbao—EIB/BIE University of the Basque Country—UPV/EHU Po Rafael Moreno no. 3 Bilbao48013 Spain Automatic Control Group—ACG Institute of Research and Development of Processes IIDP Department of Electricity and Electronics Faculty of Science and Technology University of the Basque Country—UPV/EHU Bo Sarriena s/n Leioa48080 Spain

ISBN: (纸本)9783031817236

This paper introduces a novel approach to model and stabilize a Floating Offshore Wind Turbine (FOWT) by employing Oscillating Water Columns (OWC) as an active structural control system. The innovative concept involves designing a new floating barge-like platform with integrated OWCs on opposite sides of the platform to mitigate undesired oscillations of the system. These OWCs counteract the bending forces caused by wind on the tower and waves on the barge platform. To synchronize the opposing forces with the system’s tilting, a proposed Adaptive Neuro-Fuzzy Inference System-based airflow control strategy is employed. Through manipulation of the barge platform’s pitch angle, the ANFIS airflow control system adjusts the valves on either side, opening one and closing the other accordingly. Simulation results, compared with a standard FOWT demonstrate the effectiveness of the ANFIS airflow control. It is shown to be superior in reducing platform pitching and the fore-aft translation of the tower top. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Active Structural control Air Valve Airflow control ANFIS Barge Platform Floating Offshore Wind Turbine Oscillating Water Column

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Investigating the role of an AI-based assistance system for the decision-making process of pilots– an interview study

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Transportation Research Procedia 2025年 88卷 167-175页

作者： Angela Menig Nastassja Becker Johannes P. Kleudgen Technical University Darmstadt Research Group of Work and Engineering Psychology Alexanderstraße 10 64283 Darmstadt Germany Technical University Darmstadt Institute of Flight Systems and Automatic Control Otto-Bernd-Str. 2 64287 Darmstadt Germany

The introduction of cockpit assistance systems based on Artificial Intelligence (AI) hold the potential to significantly increase flight safety and efficiency, especially in complex and time-critical situations. However, there is limited understanding how an AI-based system could effectively assist pilots in the decision-making process. This interview study investigates the decision-making process of pilots in a complex decision-making scenario with and without the support of a Level 1B AI-based assistance system (EASA Roadmap 2.0, 2023). In a complex in-flight diversion scenario, the AI-based assistance system (named Virtual Crew Assistant) provides an assessment of the risks and benefits of suitable alternates in a user-friendly interface, enabling a direct comparison of the given alternates. Semi-standardized expert interviews were conducted with 12 commercial aviation pilots. The pilots were asked to perform a decision-making process for a complex scenario - using the conventional FOR-DEC decision-making model - with and without the support of a static prototype of the Virtual Crew Assistant (VCA). During the decision-making process, the experts were instructed to think aloud, and were also requested to rate the workload for each condition. Working with the AI-based system workload was rated significantly lower than working without the AI-based system. In addition, conditions for Trust, Explainable AI, Usability and Limitations of AI-based assistance systems in the cockpit were investigated. Other possible functions of the AI-based system suggested by the experts are given and extending the human-machine interaction to higher collaborative AI-Levels is discussed.

关键词： AI-based assistance system trustworthiness explainable AI decision-making process reduced crew operations workload

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Software-defined event-based camera and vision algorithms for digitizing highly dynamic manufacturing tasks

Software-defined event-based camera and vision algorithms fo...

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2024 Low-Cost Digital Solutions for Industrial Automation, LoDiSA 2024

作者： Walker, Emily Turner, Christopher J. Oyekan, John Department of Automatic Control & Systems Engineering The University of Sheffield SheffieldS1 3JD United Kingdom Surrey Business School The University of Surrey Surrey GuildfordGU2 7XH United Kingdom Real Time & Distributed Systems Group Department of Computer Science University of York Heslington YorkYO10 5GH United Kingdom

ISBN: (纸本)9781837242672

Event-based cameras are inspired by the way the retina in the eye process information. Rather than capturing image frames at a constant rate, event cameras generate data asynchronously, based on changes in pixel value between frames. As a result, these cameras have a high spatiotemporal accuracy, low power constraints and reduced artefacts from motion blur. Hence, they represent favourable properties for digitizing highly dynamic manufacturing tasks such as machine vibrations and rapid human assembly actions. However, the costs of event-based cameras are prohibitively high for small to medium sized enterprises (SMEs). In this research, we present the development of a rig that combines low-cost visual sensors with low-cost algorithms to perform action recognition for highly dynamic manual manufacturing tasks. We applied our algorithms to achieve an action classification system via a novel threshold-based approach and in parallel use a neural network to perform classification of objects in the video feed. The results achieved demonstrated that our approach was able to successfully identify various rapid manual tasks being performed on identified objects. In addition to SMEs, our approach would be suited for providing low-cost digitization on legacy machines. © This is an open access article published by the IET under the Creative Commons Attribution License (http://***/licenses/by/3.0/).

关键词： Machine vibrations

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A Linear Parameter-Varying Approach to Data Predictive control

arXiv

引用

arXiv 2023年

作者： Verhoek, Chris Berberich, Julian Haesaert, Sofie Tóth, Roland Abbas, Hossam S. The Control Systems Group Eindhoven University of Technology Netherlands The University of Stuttgart Institute for Systems Theory and Automatic Control Germany The Institute for Electrical Engineering in Medicine Universität zu Lübeck Germany The Systems and Control Lab Institute for Computer Science and Control Hungary

By means of the linear parameter-varying (LPV) Fundamental Lemma, we derive novel data-driven predictive control (DPC) methods for LPV systems. In particular, we present output-feedback and state-feedback-based LPV-DPC methods with terminal ingredients, which guarantee exponential stability and recursive feasibility. We provide methods for the data-based computation of these terminal ingredients. Furthermore, an in-depth analysis of the application and implementation aspects of the LPV-DPC schemes is given, including application for nonlinear systems and handling noisy data. We compare and demonstrate the performance of the proposed methods in a detailed simulation example involving a nonlinear unbalanced disc system. © 2023, CC BY-NC-SA.

关键词： Predictive control systems

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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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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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