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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Tang, Zezhi Rossiter, J Anthony Dong, Yi Panoutsos, George University Of Sheffield Department Of Automatic Control And Systems Engineering SheffieldS13JD United Kingdom University Of Southampton Department Of Electronics And Computer Science Southampton United Kingdom

ISBN: (纸本)9798350340266

This paper proposes a new disturbance observer (DO)-based reinforcement learning (RL) control approach for nonlinear systems with unmatched (generalized) disturbances. While a nonlinear disturbance observer (NDO) is utilized to measure the plant uncertainties, disturbances can exist in the plant via distinct channels from those of the control signals;so-called mismatched disturbances are theoretically difficult to attenuate within the channel of the system's states. A generalized disturbance observer-based compensator is implemented to address the uncertainty cancellation problem by removing the influence of uncertainties from the output channels. Con-currently, a composite actor-critic RL scheme is utilized for approximating the optimal control policy as well as the ideal value function pertaining to the compensated system by solving a Hamilton-Jacobi-Bellman (HJB) equation for both online and offline iterations simultaneously. Stability analysis verifies the convergence of the proposed framework. Simulation results are included to illustrate the effectiveness of the proposed scheme. © 2024 IEEE.

关键词： Nonlinear systems

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

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

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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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RISC-V Extension for Optimized PWM control 27

RISC-V Extension for Optimized PWM Control

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27th International Conference on System Theory, control and Computing, ICSTCC 2023

作者： Popovici, Cosmin-Andrei Stan, Andrei Manta, Vasile-Ion Department of Computer Engineering Faculty of Automatic Control and Computer Engineering Technical University "Gheorghe Asachi" Iași Romania

ISBN: (纸本)9798350337983

This paper proposes a RISC-V extension, named SigWavy, meant to optimize the PWM control for general purpose or application specific designs. The RISC-V extension named above is a PWM control Unit with a dedicated ISA extension set designed for configuring and driving up to 32 PWM signals. The extension is integrated into RiscPwm, an updated version of our previous work, the RisCanFd SoC, for taking advantage of CAN-FD, a massively used protocol in the areas of automation and mobility. Being configured with the dedicated ISA extension or with parameters directly extracted from CAN-FD commands, the proposed solution manages to configure/reconfigure PWM channels between 4.79x and 9.18x times faster than an ARM Cortex-M7 processor, although our SoC operates with a 6x lower frequency. © 2023 IEEE.

关键词： Pulse width modulation

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Real-time Tiredness Detection System using Nvidia Jetson Nano and OpenCV 11

Real-time Tiredness Detection System using Nvidia Jetson Nan...

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11th International Conference on Information Technology and Quantitative Management, ITQM 2024

作者： Florian, Nicolae Popescu, Dumitru Hossu, Andrei Department of Automatic Control and Systems Engineering University Politehnica Bucuresti Bucharest060042 Romania Academy of Romanian Scientists Romania

In this paper, we explore how to use a Nvidia Jetson Nano and Python to create a system that detects weariness in a person's face using computer vision and machine learning techniques. The system captures the person's face in real time, preprocesses the picture to cut noise, then detects the face using Haar cascades. Next, using computer vision algorithms, characteristics associated with weariness, such as the eyes, are retrieved. These characteristics are then used to build a machine learning model that can predict weariness in the live stream feed. Lastly, using a graphical user interface, the findings are shown, and the system may be fine-tuned to increase accuracy. This device might be used in applications such as driver monitoring and traffic safety. © 2024 The Authors.

关键词： Graphical user interfaces

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ELCD-NSC2: a novel early lung cancer detection and non-small cell classification framework

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Neural Computing and Applications 2024年第24期36卷 15149-15164页

作者： Helaly, Hadeer A. Badawy, Mahmoud El-Gendy, Eman M. Haikal, Amira Y. Electrical Engineering Department Faculty of Engineering Damietta University Damietta Egypt Computers and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura Egypt Department of Computer Science and Informatics Taibah University Medina Saudi Arabia

The survival rate of lung cancer relies significantly on how far the disease has spread when it is detected, how it reacts to the treatment, the patient’s overall health, and other factors. Therefore, the earlier the lung cancer diagnosis, the higher the survival rate. For radiologists, recognizing malignant lung nodules from computed tomography (CT) scans is a challenging and time-consuming process. As a result, computer-aided diagnosis (CAD) systems have been suggested to alleviate these burdens. Deep-learning approaches have demonstrated remarkable results in recent years, surpassing traditional methods in different fields. Researchers are currently experimenting with several deep-learning strategies to increase the effectiveness of CAD systems in lung cancer detection with CT. This work proposes a deep-learning framework for detecting and diagnosing lung cancer. The proposed framework used recent deep-learning techniques in all its layers. The autoencoder technique structure is tuned and used in the preprocessing stage to denoise and reconstruct the medical lung cancer dataset. Besides, it depends on the transfer learning pre-trained models to make multi-classification among different lung cancer cases such as benign, adenocarcinoma, and squamous cell carcinoma. The proposed model provides high performance while recognizing and differentiating between two types of datasets, including biopsy and CT scans. The Cancer Imaging Archive and Kaggle datasets are utilized to train and test the proposed model. The empirical results show that the proposed framework performs well according to various performance metrics. According to accuracy, precision, recall, F1-score, and AUC metrics, it achieves 99.60, 99.61, 99.62, 99.70, and 99.75%, respectively. Also, it depicts 0.0028, 0.0026, and 0.0507 in mean absolute error, mean squared error, and root mean square error metrics. Furthermore, it helps physicians effectively diagnose lung cancer in its early stages and allows spe

关键词： Image classification

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Social NSTransformers: Low-Quality Pedestrian Trajectory Prediction

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第11期5卷 5575-5588页

作者： Jiang, Zihan Ma, Yiqun Shi, Bingyu Lu, Xin Xing, Jian Goncalves, Nuno Jin, Bo Suzhou215000 China Northeast Forestry University College of Computer and Control Engineering Harbin150000 China University of Coimbra Institute of Systems and Robotics Department of Electrical and Computer Engineering Coimbra3030-290 Portugal

This article introduces a novel model for low-quality pedestrian trajectory prediction, the social nonstationary transformers (NSTransformers), that merges the strengths of NSTransformers and spatiotemporal graph transformer (STAR). The model can capture social interaction cues among pedestrians and integrate features across spatial and temporal dimensions to enhance the precision and resilience of trajectory predictions. We also propose an enhanced loss function that combines diversity loss with logarithmic root mean squared error (log-RMSE) to guarantee the reasonableness and diversity of the generated trajectories. This design adapts well to complex pedestrian interaction scenarios, thereby improving the reliability and accuracy of trajectory prediction. Furthermore, we integrate a generative adversarial network (GAN) to model the randomness inherent in pedestrian trajectories. Compared to the conventional standard Gaussian distribution, our GAN approach better simulates the intricate distribution found in pedestrian trajectories, enhancing the trajectory prediction's diversity and robustness. Experimental results reveal that our model outperforms several state-of-the-art methods. This research opens the avenue for future exploration in low-quality pedestrian trajectory prediction. © 2024 IEEE.

关键词： Stars

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A Predictive control based Scheme for Maximum Power Extraction of PMSG based Wind Turbine systems 32

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

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

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

ISBN: (纸本)9798350399714

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. © 2023 IEEE.

关键词： controllers

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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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Study of Discrete Analog Filters with Pole Frequency Adjustment Using General Feedback Resistors 26

Study of Discrete Analog Filters with Pole Frequency Adjustm...

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26th International Conference on Digital Signal Processing and its Applications, DSPA 2024

作者： Denisenko, Darya Prokopenko, Nikolay Butyrlagin, Nikolay Ivanov, Yuri Don State Technical University Southern Federal University Department of Scientific Research Department of Automatic Control Systems Rostov-on-Don Russia Don State Technical University Department of Information Systems and Radio Engineering Rostov-on-Don Russia Southern Federal University Department of Automatic Control Systems Rostov-on-Don Russia

ISBN: (纸本)9798350361728

Three new modifications of second-order low-frequency discrete analog filters (DAFs) based on switched capacitors have been developed and studied. A distinctive feature of the DAFs under consideration is the presence of two resistors in the general feedback circuit. This allows, at constant values of the capacitances of the frequency-setting capacitors and a fixed switching frequency of electronic switches, to control the frequency of the DAF pole by changing the resistance ratio of these resistors. The basic equations for the low-pass filter gain at zero frequency, the low-pass filter gain at the pole frequency, as well as formulas for calculating the pole frequency and pole attenuation are given. In the Micro-Cap environment, computer simulation of the proposed modifications of the DAF was performed, which shows that the considered circuit solutions perform the functions of a low-pass filter. © 2024 IEEE.

关键词： Operational amplifiers

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Management of the Traffic Networks Transportation in Supplier-Customers Services by Strategic Games 11

Management of the Traffic Networks Transportation in Supplie...

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11th International Conference on Information Technology and Quantitative Management, ITQM 2024

作者： Bîlbîie, Radu Popescu, Dumitru Dimon, Catalin Department of Automatic Control and Systems Engineering UPB Bucharest Romania Academy of Romanian Scientists Ilfov 3 Bucharest050044 Romania

This paper presents an innovative approach to optimize traffic networks in a supplier-customer system based on specific strategies of game theory. The traffic network is represented as a routing configuration in which the arcs represent various possible roads between supplier and customer entities, each route having an associated transport cost for the product unit. The game structure is defined by a matrix of transport costs between the players, supplier and customer, with their corresponding strategies. Based on these costs, the game matrix is built to which the existing quantities in warehouses are added, respectively the quantities requested by the final customers. By solving the game associated to the transportation traffic network, the different strategies are proposed for choosing the optimal solution. The simulation results confirm the effectiveness of the proposed approach and recommend some performant procedures for solving the game, such as Hurwicz, Laplace and Savage, close to optimal solution. This research opens new directions for management optimization in other domains such as comunication, electrical and administrativ networks. © 2024 The Authors.

关键词： Sales

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