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A Machine-Learning Approach for Prognosis of Oscillating Water Column Wave Generators 27

A Machine-Learning Approach for Prognosis of Oscillating Wat...

引用

27th International Conference on Circuits, systems, Communications and Computers, CSCC 2023

作者： Garrido, Izaskun Lecube, Jon Mzoughi, Fares Aboutalebi, Pavam Ahmad, Irfan Cayuela, Salvador Garrido, Ailtor University of the Basque Country-UPV/EHU Automatic Control Group Acg Department of Automatic Control and Systems Engineering Bilbao Spain

ISBN: (纸本)9798350337594

Wave excitations cause structural vibrations on the Oscillating Water Columns (OWC) lowering the generated power and reducing the life expectancy. The problem of generator deterioration has been considered for the Mutriku MOWC plant and a machine learning-based approach for prognosis and fault characterization has been proposed. In particular, the use of k-Nearest Neighbors (kNN) models for predicting the time to failure of OWC generators has been proposed. The analysis is based on data collected from sensors that measure various operational parameters of the turbines. The results demonstrate that the proposed kNN model is an excellent choice for reducing maintenance costs by enabling scheduling months in advance. The model's high accuracy in predicting generator failures allows for timely and cost-effective maintenance, preventing costly breakdowns and improving turbine efficiency. These results highlight the potential of machine learning-based approaches for addressing maintenance challenges in the energy sector and underscore the importance of proactive strategies in reducing operational costs and maximizing energy production. © 2023 IEEE.

关键词： Cost effectiveness

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Hybrid offshore wind turbines: control-oriented modeling approaches 6th

Hybrid offshore wind turbines: Control-oriented modeling app...

引用

6th International Conference on Renewable Energies Offshore, RENEW 2024

作者： Ahmad, I. M’zoughi, F. Aboutalebi, P. Garrido, I. Garrido, A.J. Automatic Control Group—ACG Institute of Research and Development of Processes—IIDP Department of Automatic Control and Systems Engineering Engineering School of Bilbao—EIB/BIE Faculty of Engineering of Bilbao—EIB/BIE University of the Basque Country—UPV/EHU Bilbao Spain

ISBN: (纸本)9781032905570

In the pursuit of sustainable electricity generation from offshore wind and wave energy, the combination of Floating Offshore Wind Turbines (FOWTs) and Oscillating Water Columns (OWCs) has emerged as a promising solution to enhance the working lifespan of this kind of systems. This study introduces a control-focused modeling approach, using empirical data collected from the widely accepted FAST environment, to implement advanced control laws for these integrated platforms. Leveraging Long Short-Term Memory (LSTM) and Artificial Neural Networks (ANN), the research yields predictive models that effectively capture the platform pitch dynamics so as to optimize control strategies. By integrating advanced machine learning techniques, these approaches address the challenges of modeling floating offshore structures in dynamic environments. In this sense, the neuro-estimators developed in this study closely match the original plant results, offering researchers a straightforward way to implement complex control schemes that could hardly be implemented over the original non-linear system. © 2025 The Author(s).

关键词： Offshore wind turbines

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A Machine-Learning Approach for the Development of a FOWT Model Integrated with Four OWCs 26

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

引用

26th International Conference on Circuits, systems, Communications and Computers, CSCC 2022

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

ISBN: (纸本)9781665481861

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. © 2022 IEEE.

关键词： Wind

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Robust Sliding Mode control of a Quadrotor With Disturbance Rejection for Enhanced Stability and Performance 6

Robust Sliding Mode Control of a Quadrotor With Disturbance ...

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6th International Conference on Robotics and Automation in Industry, ICRAI 2024

作者： Ullah, Hameed Zarin, Owais Ahmad, Irfan Ahmad, Sarfraz Abbas, Ansar Lippiello, Vincenzo University of Naples Federico II Department of Electrical Engineering and Information Technology Naples Italy Riphah International University Department of Electrical Engineering Islamabad Pakistan School of Bilbao - EIB/BIE University of the Basque Country - UPV/EHU Automatic Control Group ACG Department of Automatic Control and Systems Engineering Rafael Moreno 3 Bilbao48013 Spain CEME Department of Electrical Engineering Islamabad Pakistan

ISBN: (纸本)9798350355703

This research presents a comprehensive analysis of quadrotor stabilization and trajectory tracking control using Proportional-Integral-Derivative (PID) and Sliding Mode control (SMC) with integrated disturbance rejection. The nonlinear dynamics of the quadrotor are formulated using the Newton-Euler approach, accounting for six degrees of freedom. The PID controller is implemented as a baseline, while the SMC is designed for enhanced robustness to model uncertainties and external perturbations, with a disturbance observer for managing time-varying disturbances. A rigorous Lyapunov stability proof ensures global asymptotic stability of the SMC-controlled system. Extensive simulations evaluate both controllers in terms of tracking accuracy, control effort, and robustness to external disturbances. Results show that SMC outperforms PID in dis-turbance rejection, tracking accuracy, and robustness, making it ideal for UAV applications in complex environments. © 2024 IEEE.

关键词： Sliding mode control

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Online Residual Learning from Offline Experts for Pedestrian Tracking 63

Online Residual Learning from Offline Experts for Pedestrian...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Vlachos, Anastasios Tsiamis, Anastasios Karapetyan, Aren Balta, Efe C. Lygeros, John Eth Zürich Automatic Control Laboratory Department of Information Technology and Electrical Engineering Zürich8092 Switzerland Control and Automation Group Inspire ZürichAG 8005 Switzerland The Automatic Control Laboratory Switzerland

ISBN: (纸本)9798350316339

In this paper, we consider the problem of predicting unknown targets from data. We propose Online Residual Learning (ORL), a method that combines online adaptation with offline-trained predictions. At a lower level, we employ multiple offline predictions generated before or at the beginning of the prediction horizon. We augment every offline prediction by learning their respective residual error concerning the true target state online, using the recursive least squares algorithm. At a higher level, we treat the augmented lower-level predictors as experts, adopting the Prediction with Expert Advice framework. We utilize an adaptive softmax weighting scheme to form an aggregate prediction and provide guarantees for ORL in terms of regret. We employ ORL to boost performance in the setting of online pedestrian trajectory prediction. Based on data from the Stanford Drone Dataset, we show that ORL can demonstrate best-of-both-worlds performance. © 2024 IEEE.

关键词： Prediction models

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Analysis of the Findings of the Study of the Time to Saturation of Current Transformer Magnetic Circuits Located at Electric Power Facilities

Analysis of the Findings of the Study of the Time to Saturat...

引用

2024 International Ural Conference on Electrical Power engineering, UralCon 2024

作者： Yablokov, Andrey Panashchatenko, Anton Ivanovo State Power Engineering University ISPU Department of Electric Power Systems Automatic Control Ivanovo Russia

ISBN: (纸本)9798350386028

Emergencies associated with incorrect operation of relay protection and automation (RPA) devices due to saturation of current transformers (CTs) can lead to great economic damage. The article presents an analysis of regulatory and technical documentation containing requirements for the quality of CT functioning in transient modes, statistical data on the results of calculations performed in accordance with the requirements of GOST R 58869-2019, as well as an analysis of the correctness of the assumptions introduced by it. To calculate the time to CTs saturation a special program was developed that automates the calculation methods, taking into account the assumptions focused on performing the manual calculations. The program takes into account the variation of the short circuit switching angle, the phase difference of the short circuit currents flowing through the branches feeding the short circuit point, the calculation of all CTs of a three-phase group with automatic selection of the worst result. The results obtained allow us to conclude about the relative number of CTs that do not meet the requirements of GOST R 58869-2019, the need to modernize existing methods and possible directions for such modernization. In addition, the article provides recommendations on the creation of automatic specialized software systems that can be used in the work of design, operating and research entities when they calculate the time to saturation of the CT magnetic circuits. © 2024 IEEE.

关键词： Transformer protection

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A Machine-Learning Approach for Prognosis of Oscillating Water Column Wave Generators

A Machine-Learning Approach for Prognosis of Oscillating Wat...

引用

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

作者： Izaskun Garrido Jon Lecube Fares Mzoughi Pavam Aboutalebi Irfan Ahmad Salvador Cayuela Ailtor Garrido Department of Automatic Control and Systems Engineering Automatic Control Group ACG University of the Basque Country-UPV/EHU Bilbao Spain

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Hydrodynamic and Static Stability Analysis of a Hybrid Offshore Wind-Wave Energy Generation: An Expansion of Semisubmersible Floating Wind Turbine Concept 15th

Hydrodynamic and Static Stability Analysis of a Hybrid Offsh...

引用

15th European Wave and Tidal Energy Conference, EWTEC 2023

作者： Aboutalebi, Payam Garrido, Aitor J. Garrido, Izaskun Nguyen, Dong Trong Gao, Zhen Department of Marine Technology Trondheim7491 Norway Automatic Control Group–ACG Institute of Research and Development of Processes–IIDP Department of Automatic Control and Systems Engineering Faculty of Engineering of Bilbao University of the Basque Country–UPV/EHU Spain School of Naval Architecture Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai200240 China

Marine structures like Floating Wind Turbine (FWT) is exposed to the oncoming waves and wind that can cause oscillatory motions within the system. These undesired oscillations can have negative impacts on the efficiency of the system, reduce its lifespan, hinder energy extraction, increase stress levels, and raise maintenance costs. To mitigate these negative impacts, the integration of Wave Energy Converters (WECs) into the FWT system has been proposed. This hybrid system may be capable of extracting coupled wind-wave energy and transferring electrical power to the shared grid. This paper presents an investigation of the use of Oscillating Water Columns (OWCs), a type of WECs, within a FWT system. The purpose of using an OWC is to increase the hydrodynamic damping and reduce the resonant motions of the floating wind turbines under environmental loads, including both wind and wave loads. This is because the wave energy from OWC would be very small as compared to the wind energy. However, OWCs can provide a damping source for reducing the resonant motions of the floater, especially the pitch resonant motions. This would be very beneficial for the power performance of the floating w ind turbine and the structural design of the floater. T he p urpose of this paper is to redesign the original FWT platform to accommodate the additional OWCs by considering the hydrostatic stability and hydrodynamics since the new elements, the OWCs, can significantly change the response of the platform. The redesign of the original FWT involves the integration of OWCs within two out of three columns of an existing semisubmersible platform for a 12 MW FWT. To do this, two moonpools, which are consistent with OWC air chambers, have been created within two columns of the FWT. The water ballast was designed for the columns with and without OWCs. After that the redesign is done hydrostatic stability and hydrodynamics analyses are evaluated. The hydrodynamics properties are discussed in terms o

关键词： Tidal power

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Experimental Validation of the Capture Chamber Model in Mutriku MOWC Wave Power Plant

Experimental Validation of the Capture Chamber Model in Mutr...

引用

OCEANS

作者： Aitor J. Garrido Jon Lekube Amparo Villasante Izaskun Garrido Automatic Control Group - ACG Inst. of Research and Development of Processes - IIDP Automatic Control and Systems Engineering Dept. Faculty of Engineering of Bilbao University of the Basque Country (UPV/EHU) Bilbao Spain Automatic Control Group - ACG BiMEP – Biscay Marine Energy Armintza Bizkaia Spain Automatic Control Group - ACG Faculty of Engineering of Bilbao University of the Basque Country (UPV/EHU). Bilbao Spain

ISBN: (数字)9798350362077

ISBN: (纸本)9798350362084

Ocean wave energy has de potential to satisfy 15% of EU energy demand, cutting 136 MT/MWh off the CO2 emissions by 2050, as stated by the EU Energy Road Map. Analogously, the Spanish Renewable Energies Plan specifically highlighted the Spanish marine energy potential with special emphasis in wave energy. In this context, Oscillating Water Column (OWC) converters are maybe nowadays the most promising wave energy converters, with the potential capability of sea energy harnessing from diverse on-shore and floating structures. This paper presents an analytic modeling of the wave capture chamber for a fixed on-shore OWC wave power plant. The model is particularized and parameterized for the case of the Mutriku MOWC wave power plant, located in the Spanish Basque Country coast, and then validated using both measured real wave entry data and experimental generated output power from the plant

关键词： Renewable energy sources Power measurement Wave power Roads Sea measurements Predictive models Particle measurements

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Unsupervised Learning-Based Methodology for Detection of Postural Anomalies in Wheelchair Users

Unsupervised Learning-Based Methodology for Detection of Pos...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Vermander, Patrick Mancisidor, Aitziber Fortino, Giancarlo Cabanes, Itziar Gravina, Raffaele Department of Automatic Control and System Engineering Bilbao Spain Department of Informatics Modeling Electronics and Systems Engineering Rende Italy

ISBN: (纸本)9798350337020

Postural monitoring in wheelchair users is a topic of growing interest. The detection of changes in the sitting patterns of these patients may serve to detect changes in their functional status and be able to adapt rehabilitation early. For this reason, this paper presents a methodology for the detection of specific postural anomalies that, unlike previous works, adopts unsupervised learning. The proposed methodology involves data dimensionality reduction using Principal Component Analysis, and the application of K-means clustering to group different normal posture states. The anomalies are detected using a threshold approach, where data points that fall outside a certain threshold are considered as anomalies. The results show that the methodology is effective in identifying anomalies with a high degree of accuracy (around 90%). © 2023 IEEE.

关键词： Anomaly detection Kmeans PCA Postural monitoring Wheelchair

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