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Optica Sensing Congress 2023, AIS, FTS, HISE, Sensors, ES 2023 - Part of Optical Sensors and Sensing Congress 2023

作者： Leelasirinuwong, Mintra Denkasineecharoen, Phebe Yungyuentrrakoon, Pin Jitpratak, Pannathorn Kongsawang, Nuntaporn Pathak, Akhilesh Kumar Viphavakit, Charusluk Faculty of Engineering Chulalongkorn University Bangkok10330 Thailand Biomedical Engineering Program Faculty of Engineering Chulalongkorn University Bangkok10330 Thailand Intelligent Control Automation of Process Systems Research Unit Faculty of Engineering Chulalongkorn University Bangkok10330 Thailand

A molecular imprinted polymer-based optical sensor is proposed to detect methanol. The sensor is tested with different concentrations of methanal vapour for sensitivity and ethanol for selectivity. The result shows a ... 详细信息

ISBN: (纸本)9781957171241

关键词： Optical sensors

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Data-Driven Group Formation control of Cyber-Physical Systems via Distributed Cloud Computing

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 341-350页

作者： Ren, Hongru Long, Yinren Li, Hongyi Huang, Tingwen Guangdong University of Technology School of Automation Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Control Guangdong Provincial Key Laboratory for Intelligent Decision and Cooperative Control Guangzhou510006 China Southwest University College of Electronic and Information Engineering Chongqing400715 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

This paper investigates the group formation control problem for cyber-physical systems (CPSs) with random communication constraints. The distributed cloud computing system is constructed to divide agents into groups and establish communication between agents. A data-driven predictive control strategy is proposed by combining networked predictive control and model-free adaptive control method. The desired group formation control performance can be achieved and the three-channel random communication constraints of CPSs are actively compensated. Thisstrategy does not require the system model and relies solely on the system's I/O data for adaptive learning. Further analyses concludes the conditions for simultaneous reach stability and group formation of the closed-loop CPSs using the data-driven predictive control strategy. The effectiveness of the proposed strategy is validated by simulation results. © 2023 IEEE.

关键词： Distributed cloud

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The Rotary Flexible Joint – A Holistic View from Modeling and control to Observer Design and Experiments

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IFAC-PapersOnLine 2023年第2期56卷 7567-7572页

作者： Simon Helling Thomas Meurer Automation and Control Group Faculty of Engineering Kiel University

A two degrees of freedom (2DOF) control for a lab-scale vertically-mounted rotary flexible joint is addressed to realize a benchmark example for nonlinear control education and experimentation. To this end, the mathematical model is derived based on the Euler-Lagrange equations. Further insight into the model is given by addressing the relationship between the two translational springs and their approximation as a single torsion spring. The model is known to be differentially flat, which facilitates a feedforward control design by means of the flat parameterization. Furthermore, a state-feedback controller is introduced to stabilize the desired trajectory. State information is reconstructed using a Luenberger-type observer. Both the state-feedback controller and the Luenberger-type observer are designed based on a linear time-varying (LTV) approximation obtained using a linearization around the flat state parameterization of the system. The 2DOF design is illustrated using experimental results.

关键词： Nonlinear control feedback control feedforward control observers pole assignment

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Augmented Reality Application in Digital automation Laboratory

Augmented Reality Application in Digital Automation Laborato...

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2023 International Symposium on Electrical and Electronics engineering, ISEE 2023

作者： Khang, Nguyen Trong Tran, Ngoc-Huy Phan, Nguyen-Phuc-Quoc VNU-HCM Faculty of Electrical & Electronics Engineering Department of Control & Automation Ho Chi Minh City Viet Nam

ISBN: (纸本)9798350315486

Traditional automation engineering education using physical training equipment while quite effective, suffers from several limitations in the case there is no equipment access, which can be due to many reasons such as social distancing or financial difficulties. This article proposes a solution to overcome these limitations with the combinational use of mixed reality (MR), which helps the student get used to training equipment they have no access to, and augmented reality (AR), which brings intuitive visualization into real equipment practice. © 2023 IEEE.

关键词： Augmented reality

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Two-Degree-of-Freedom Feedback Loop Factorization controller for Oscillating Plant with Uncertain Time Delay and Astatism Using Structured Singular Value

Two-Degree-of-Freedom Feedback Loop Factorization Controller...

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2024 International Conference on control, automation and Diagnosis, ICCAD 2024

作者： Dlapa, Marek Tomas Bata University In Zlin Faculty of Applied Informatics Department of Automation and Control Engineering Nad Stranemi 4511 Zlin760 05 Czech Republic

ISBN: (纸本)9798350361025

Application of Robust control Toolbox for Time Delay Systems implemented in the Matlab system to the oscillating plant with uncertain time delay and astatism using the D-K iteration and algebraic approach. The algebraic approach combines the structured singular value, algebraic theory and algorithm of global optimization solving remaining issues in structured singular value framework. The algorithm for global optimization can be alternated with direct search methods such as Nelder-Mead simplex method giving solutions for problems with one local extreme. As a global optimization method, Differential Migration is used proving to be reliable in solving this type of problems. The D-K iteration represents a standard method in the structured singular value theory. The results obtained from the D-K iteration are compared with the algebraic approach. © 2024 IEEE.

关键词： Global optimization

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A Deep Learning Approach for Faults Recognition of Dissolved Oxygen Sensor in Wastewater Treatment Plants 28

A Deep Learning Approach for Faults Recognition of Dissolved...

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28th IEEE International Conference on Emerging Technologies and Factory automation, ETFA 2023

作者： Ghinea, Liliana Maria Miron, Mihaela Ratnaweera, Harsha Electrical Engineering and Electronics Faculty of Automation Computers Department of Automatic Control and Electrical Engineering Department Galaţi Romania Computers Electrical Engineering and Electronics Faculty of Automation Department of Computer Science and Information Technology Galaţi Romania Norwegian University of Life Sciences Faculty of Science and Technology Oslo Norway

ISBN: (纸本)9798350339918

Fault diagnosis in wastewater treatment plants (WWTPs) is important to protect communities and ecosystems from toxic elements discharged into water. In this sense, fault identification of sensors plays an important role as they are the key components of the water plants control, especially because environmental legislation is very strict when referring to failures or anomalies in WWTPs. This paper analyzes the performances of two Deep Learning models, a Feedforward Neural Network (FFNN) and a 1D Convolution Neural Network (1DCNN) for identifying five operating states of the dissolved oxygen (DO) sensor: normal and faulty (bias, stuck, spike and precision degradation faults). The experiments were conducted on the Benchmark Simulator Model No 2 (BSM2) developed by the IWA Task Group. The performance of the Deep Learning (DL) classifiers was evaluated via accuracy, precision, recall, and F1-score metrics. The best overall classification accuracy was obtained by FFNN, 98.32% for training and 98.30% for testing. © 2023 IEEE.

关键词： Wastewater treatment

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Robust controller Design with Two-Degree-of-Freedom Feedback Loop Factorization for Oscillating Plant with Uncertain Time Delay

Robust Controller Design with Two-Degree-of-Freedom Feedback...

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2023 International Conference on control, automation and Diagnosis, ICCAD 2023

作者： Dlapa, Marek Tomas Bata University in Zlin Faculty of Applied Informatics Department of Automation and Control Engineering Zlin760 05 Czech Republic

ISBN: (纸本)9798350347074

Application of Robust control Toolbox for Time Delay Systems implemented in the Matlab system to the oscillating plant with uncertain time delay using the D-K iteration and algebraic approach. The algebraic approach combines the structured singular value, algebraic theory and algorithm of global optimization solving remaining issues in structured singular value framework. The algorithm of global optimization can be alternated with direct search methods such as Nelder-Mead simplex method giving solutions for problems with one local extreme. As a global optimization method, Differential Migration is used proved to be reliable in solving this type of problems. The D-K iteration represents a standard method in the structured singular value theory. The results obtained from the D-K iteration are compared with the algebraic approach. © 2023 IEEE.

关键词： Global optimization

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Influences of Inhomogeneous Spatial Distribution of Global Oceanic Atmospheric Refractivity on LF Groundwave Propagation Delay

Influences of Inhomogeneous Spatial Distribution of Global O...

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2024 International Applied Computational Electromagnetics Society Symposium, ACES-China 2024

作者： Wang, Dan-Dan Lu, Qi-Zirui Han, Chao Pu, Yu-Rong Yang, Rui-Hong Bai, Pei-Rui Shandong University of Science and Technology College of Electronic and Information Engineering Qingdao China Xi'an University of Technology Faculty of Automation and Information Engineering Xi'an China Beijing Aerospace Automatic Control Institute Beijing China

ISBN: (纸本)9798350355581

Atmospheric refractivity affects the propagation delay of low-frequency (LF) groundwave in the realistic ocean environment. In this paper, a parabolic equation (PE) model based on the ERA5 meteorological reanalysis dataset is applied to analyze the influences of inhomogeneous spatial distribution of global oceanic atmospheric refractivity on LF groundwave propagation delay. The global oceanic atmospheric refractivity is derived from the meteorological quantities given by the ERA5 reanalysis dataset. It is found that the global oceanic surface atmospheric refractivity varies systematically with latitude in the range of 290∼300 N-unit to 380∼400 N-unit, which in turn leads to the variation of LF groundwave propagation delay reaching hundredth nanosecond for 1000 km-long propagation path. © 2024 IEEE.

关键词： global oceanic atmospheric refractivity low-frequency (LF) groundwave propagation parabolic equation (PE)

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Texture Analysis of Breast US Images Using Morphological Transforms, Hausdorff Dimension and Bagging Ensemble Method 32

Texture Analysis of Breast US Images Using Morphological Tra...

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32nd Mediterranean Conference on control and automation, MED 2024

作者： Tabacaru, Gigi Moldovanu, Simona Barbu, Marian 'Dunarea de Jos' University of Galati Faculty of Automation Computers Electrical Engineering and Electronics Department of Automatic Control and Electrical Engineering Romania 'Dunarea de Jos' University of Galati Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics Romania Dunarea de Jos University of Galati The Modelling & Simulation Laboratory Galati800008 Romania

ISBN: (纸本)9798350395440

In this work, an attempt is made for the first time to use the measurement pattern generated by morphological transformation quantified by Hausdorff fractal dimension (HFD) and classified with ensemble learning based on bagging. The proposed work uses three morphological transformations for image preprocessing: hit-and-miss transform (HMT), white (WHT), and black top-hat (BHT). The pattern texture of US breast images is described by extracting the HFD from the regions of interest (ROI) after the ultrasound (US) images have been preprocessed. The main objective of this study was achieved by comparatively analyzing the classification performance of features using the Random Forest (RF), Extra Trees (ET) classifier, and bagging ensemble method based on XGBoot classifier. In presented study, the XGBoost classifier and BHT image processing method give an accuracy of 89.8% in a binary classification, benign versus malignant breast cancer. © 2024 IEEE.

关键词： Fractal dimension

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Performance Comparison of Lightweight CNN Models for Drone Collision Avoidance Dataset 20

Performance Comparison of Lightweight CNN Models for Drone C...

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20th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2023

作者： Zufar, Rifqi Nabila Banjerdpongchai, David Chulalongkorn University Center of Excellence in Intelligent Control Automation of Process Systems Department of Electrical Engineering Faculty of Engineering 254 Phayathai Road Bangkok Pathumwan10330 Thailand

ISBN: (纸本)9798350310467

Collision Avoidance System (CAS) is important for drone safety. CAS consists of three steps e.g., obstacle sensing, collision prediction, and collision avoidance. Collision prediction enables drones to gain information, process information, and estimate whether the object has a risk of collision. Convolution Neural Network (CNN) is one of the methods that can be employed for collision prediction. However, CNN is a method that needs a large data in the training. Dario Pedro et al. provided a dataset called the CoLANet dataset that consists of VDOs of collision drones. Subsequently, they proposed a new algorithm called Neural Network Pipeline which has a Convolution Neural Network (CNN) part to extract the feature from a couple of images. CNN extracts images by using MobileNetV2 as a pre-trained model. They chose MobileNetV2 due to training performance from another dataset. This paper aims to assess the performance of lightweight CNN models using the CoLANet dataset. The models will be trained on the Keras library with parameters of fewer than ten million. The models will be validated by Confusion Matrix and Receiver Operating Characteristics. In conclusion, we examine which pre-trained CNN model has the best performance and suggest ongoing work. © 2023 IEEE.

关键词： Drones

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