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Investigation of a Novel Atmospheric Pressure Microwave Cold Plasma Torch and Its Characteristics

Chemical Research in Chinese Universities 2024年第6期40卷 1282-1289页

作者： LI Yarui BAI Yiwen YU Dengjie WANG Rongyao MU Ying JIN Wei YU Bingwen Research Center for Analytical Instrumentation Institute of Cyber-Systems and ControlCollege of Control Science and EngineeringZhejiang UniversityHangzhou 310027P.R.China Research Center for Analytical Instruments and Intelligent Systems Huzhou Institute of Zhejiang UniversityHuzhou 313000P.R.China

This study proposes a coaxial structure atmospheric pressure microwave cold plasma device that utilizes argon as the main working *** achieves stable formation of atmospheric pressure cold plasma jet at low power (<50 W) with a jet length ranging from 1 mm to 32 *** paper analyzes the composition of the cold plasma using spectroscopy and investigates its composition changes at different positions along the *** also studies the appearance and reaction composition of the plasma filament under different shielding ***,it explores the effects of continuous and modulated microwave power on the length,appearance,and composition of the plasma ***,it examines the bactericidal effect of the plasma filament on Escherichia coli under various gas conditions,providing a foundation for further application research.

关键词： Microwave cold plasma Spectral analysis Modulated microwave source Sterilization

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Photographic Analysis and Optical Diagnosis of Kilowatt Microwave Plasma Torch with Air Carrier Gas

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Chemical Research in Chinese Universities 2023年第6期39卷 1051-1057页

作者： YU Dengjie YU Bingwen ZHANG Xuchen HUANG Shiluo YING Yangwei YAN Yuwei JIN Yining JIN Wei Research Center for Analytical Instrumentation Institute of Cyber-Systems and ControlCollege of Control Science and EngineeringZhejiang UniversityHangzhou 310058P.R.China Research Center for Analytical Instruments and Intelligent Systems Huzhou Institute of Zhejiang UniversityHuzhou 313002P.R.China Faculty of Engineering University of Alberta116 St.and 85 Ave.EdmontonAlbertaCanada

The spatiotemporal motion characteristics of the kilowatt argon microwave plasma torch with the air carrier gas(kW-AC-ArMPT)and the behavior of the plasma filaments are investigated with a digital single-lens reflex(SLR)camera and a high-speed *** with the introduction of the air,both the volume of the central channel and the rotational frequency of the plasma filament are ***,the excitation temperature(Texc),rotational temperature(Trot),and density of electron number(ne)of the kW-AC-ArMPT are measured with optical *** is clearly shown that the introduction of air contributed to the rise of Trot and ne of the plasma,which is beneficial to improving the analytical performance of the *** the detection limits of some heavy metal elements are measured by kW-AC-ArMPT,which are in the ppb *** experimental results show that the kW-ArMPT has a high tolerance to air injection at least 1.0 L/min,which allows the direct extraction of air from the environment for analysis and therefore has the potential for online and in-situ detection of ambient air quality and industrial exhaust gases.

关键词： Air carrier gas Microwave plasma torch Photographic analysis Optical diagnosis

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Color liquid crystal grating based color holographic 3D display system with large viewing angle

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Light(Science & Applications) 2024年第1期13卷 103-112页

作者： Di Wang Yi-Long Li Fan Chu Nan-Nan Li Zhao-Song Li Sin-Doo Lee Zhong-Quan Nie Chao Liu Qiong-Hua Wang School of Instrumentation and Optoelectronic Engineering Beihang UniversityBeijing 100191China State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China Display Technology Research Center Seoul National UniversityGwanak-ro 1Gwanak-guSeoul 08826Republic of Korea Key Lab of Advanced Transducers and Intelligent Control System Ministry of EducationTaiyuan University of TechnologyTaiyuan 030024China

Holographic 3D display is highly desirable for numerous applications ranging from medical treatments to military ***,it is challenging to simultaneously achieve large viewing angle and high-fidelity color reconstruction due to the intractable constraints of existing ***,we conceptually propose and experimentally demonstrate a simple and feasible pathway of using a well-designed color liquid crystal grating to overcome the inevitable chromatic aberration and enlarge the holographic viewing angle,thus enabling large-viewing-angle and color holographic 3D *** use of color liquid crystal grating allows performing secondary diffraction modulation on red,green and blue reproduced images simultaneously and extending the viewing angle in the holographic 3D display *** principle,a chromatic aberration-free hologram generation mechanism in combination with the color liquid crystal grating is proposed to pave the way for on such a superior holographic 3D *** proposed system shows a color viewing angle of~50.12°,which is about 7 times that of the traditional system with a single spatial light *** work presents a paradigm for achieving desirable holographic 3D display,and is expected to provide a new way for the wide application of holographic display.

关键词： holographic angle crystal

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Investigation and Simulation of Atmospheric Pressure Microwave Cold Plasma Torch

Investigation and Simulation of Atmospheric Pressure Microwa...

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IEEE International Conference on Plasma Science (ICOPS)

作者： Y. Li Y. Bai R. Zhang Y. Shao W. Jin B. Yu Research Center for Analytical Instrumentation Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou China Research Center for Analytical Instruments and Intelligent Systems Huzhou Institute of Zhejiang University Huzhou China

ISBN: (数字)9798350360912

ISBN: (纸本)9798350360929

The microwave coaxial structure has been widely used for plasma excitation, and microwave power and working gas are key factors that affect its practical application. This paper proposes an atmospheric pressure microwave cold plasma torch operating at 2.45 GHz. It employs a segmented coaxial structure combined with narrowing at the opening to enhance the electric field intensity. It achieves cold plasma jet discharges of various gases, including air, nitrogen, argon, and helium, at low power (<30 W).

关键词： Microwave integrated circuits Plasma jets Atmospheric modeling Discharges (electric) Plasmas Nitrogen Helium

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Enhancing Traffic Flow Forecasting with Spatio-Temporal Information: A Case Study on Highway Networks in Belgium 8

Enhancing Traffic Flow Forecasting with Spatio-Temporal Info...

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8th International Conference on instrumentation, control, and Automation, ICA 2023

作者： Fathurrahman, Muhammad Farhan Catteeuw, Arne Gautama, Sidharta Aguirre, Angel L. Joelianto, Endra Sutarto, Herman Y. Ghent University Engineering and Product Design Department of Industrial Systems Ghent Belgium Department of Intelligent System Bandung Indonesia FlandersMake@UGent-Corelab ISyE Lommel Belgium Institut Teknologi Bandung Instrumentation and Control Research Group Faculty of Industrial Technology Bandung Indonesia

ISBN: (纸本)9798350301274

As the number of vehicles continues to increase every year, it is crucial to monitor traffic conditions effectively. Traffic forecasting serves as a valuable method in traffic management to support decision making. This study investigates the impact of utilizing spatio-Temporal data for traffic flow forecasting, as opposed to forecasting each location individually. We compare spatio-Temporal Long Short-Term Memory (LSTM), a machine-learning technique that utilizes spatially correlated sensor data in a network, and compare this to conventional LSTM and Seasonal ARIMA (SARIMA). Experiments have been conducted on counting loop data of a highway network in Belgium. We have investigated the performances of the forecasting model for different prediction horizons. The results show that spatial information improves the performance of the forecasting model and reduces the training time required. Further analysis show that the spatio-Temporal LSTM improves majorities of detectors while the minorities detectors are degraded which imply the importances of network selection. The computational load of the spatio-Temporal LSTM model is minimally impacted by the number of sensors in the network thus making it scalable. The results show that longer prediction horizons degrade the forecasting performance but the impact up to a 12 hour-horizon is not significant. © 2023 IEEE.

关键词： Long short-term memory

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Resilient Event-Triggered Model Predictive control for Adaptive Cruise control Under Sensor Attacks

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 807-809页

作者： Zhijian Hu Rong Su Kai Zhang Zeyuan Xu Renjie Ma School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore Key Laboratory of Ultra-Precision Intelligent Instrumentation Ministry of Industry and Information Technologyand the Center of Ultra-Precision Optoelectronic Instrument EngineeringHarbin Institute of TechnologyHarbin 150001China Department of Control Science and Engineering Harbin Institute of TechnologyHarbin 150001China Department of Chemical and Biomolecular Engineering National University of SingaporeSingapore 117585Singapore State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin 150001China IEEE

Dear Editor,This letter addresses the resilient model predictive control(MPC)problems for adaptive cruise control(ACC)systems under sensor *** the light of vulnerabilities of ACC systems to sensor attacks,an intrusion detection mechanism is proposed at the controller side to distinguish abnormal ***,the robust control gains are derived to design the terminal region constraint for MPC.

关键词： Trigger Event constraint

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Fault Tolerant Dynamic Task Assignment for UAV-based Search Teams

arXiv

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arXiv 2024年

作者： Nasir, Ali AlDurgam, Mohammad Interdisciplinary Research Center for Intelligent Manufacturing and Robotics KFUPM Dhahran Saudi Arabia Control and Instrumentation Engineering Department KFUPM Dhahran Saudi Arabia Interdisciplinary Research Center for Smart Mobility and Logistics KFUPM Dhahran Saudi Arabia Industrial and Systems Engineering Department KFUPM Dhahran Saudi Arabia

This research offers a novel framework for dynamic task assignment for unmanned aerial vehicles (UAVs) in cooperative search settings. Notably, it incorporates post-fault UAV capabilities into job assignment techniques, assuring operational dependability in the event of sensor and actuator failures. A significant innovation is the utilization of UAV battery charge to assess range relative to search objectives, hence improving job distribution while conserving battery life. This model integrates repair, recharge, and stochastic goal recurrence, hence increasing its real-world applicability. Using stochastic dynamic programming, this method makes it simpler to determine optimal assignment policies offline so they may be implemented rapidly online. This paper emphasizes the holistic aspect of the proposed model, which connects high-level task rules to low-level control capabilities. A simulation-based case study proves its usefulness, highlighting its robustness in fault-prone and battery-variable settings. Overall, this paper proposes and demonstrates a comprehensive method for assigning UAV tasks that integrates defect awareness, battery management, and multilayer control through the use of stochastic dynamic programming. © 2024, CC BY.

关键词： Stochastic systems

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Optimized Task Assignment and Predictive Maintenance for Industrial Machines using Markov Decision Process

arXiv

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arXiv 2024年

作者： Nasir, Ali Mekid, Samir Sawlan, Zaid Alsawafy, Omar Control and Instrumentation Engineering Department KFUPM Dhahran Saudi Arabia Mechanical Engineering Department KFUPM Dhahran Saudi Arabia Mathematics Department KFUPM Dhahran Saudi Arabia Systems Engineering Department Dhahran Saudi Arabia Interdisciplinary Research Center for Intelligent Manufacturing and Robotics KFUPM Dhahran Saudi Arabia

This paper considers a distributed decision-making approach for manufacturing task assignment and condition-based machine health maintenance. Our approach considers information sharing between the task assignment and health management decision-making agents. We propose the design of the decision-making agents based on Markov decision processes. The key advantage of using a Markov decision process-based approach is the incorporation of uncertainty involved in the decision-making process. The paper provides detailed mathematical models along with the associated practical execution strategy. In order to demonstrate the effectiveness and practical applicability of our proposed approach, we have included a detailed numerical case study that is based on open source milling machine tool degradation data. Our case study indicates that the proposed approach offers flexibility in terms of the selection of cost parameters and it allows for offline computation and analysis of the decision-making policy. These features create and opportunity for the future work on learning of the cost parameters associated with our proposed model using artificial intelligence. © 2024, CC BY.

关键词： Optimization

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Renewable Power Generation Maximization for UAVs with Adaptive Sliding Mode control

Renewable Power Generation Maximization for UAVs with Adapti...

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International Conference on Renewable Energy Research and Applications (ICRERA)

作者： Khalid Alfuwail Ali Nasir Md Shafiullah Ayman Abdallah Control & Instrumentation Engineering Department King Fahd University of Petroleum & Minerals (KFUPM) Dhahran Eastern Province Saudi Arabia Control & Instrumentation Engineering Department IRC Intelligent Manufacturing and Robotics (IRC-IMR) King Fahd University of Petroleum & Minerals (KFUPM) Dhahran Eastern Province Saudi Arabia Control & Instrumentation Engineering Department IRC for Sustainable Energy Systems (IRC-SES) King Fahd University of Petroleum & Minerals (KFUPM) Dhahran Eastern Province Saudi Arabia Aerospace Engineering Department IRC for Aviation & Space Exploration (IRC-ASE) King Fahd University of Petroleum & Minerals (KFUPM) Dhahran Eastern Province Saudi Arabia

ISBN: (数字)9798350375589

ISBN: (纸本)9798350375596

The demand for efficient and Fuel consumption alternative renewable energy sources in the aviation sector has led to the exploration of advanced technologies such as Ram Air Turbines (RATs). RATs are critical in applications requiring power generation in emergency scenarios that may happen to un-manned aerial vehicles (UAVs). However, the primary challenge lies in optimizing the performance of the RATs, such as power output and operational stability, under varying and unpredictable wind conditions. Traditional control methods often fail to adapt to these dynamic environments. This paper underscores the necessity of utilizing a recurrent neural network (RNN) to detect uncertain wind turbine dynamics; a sliding mode control rule is created in the suggested controller to monitor the optimal turbine rotation speed. Next, an online update technique is developed to provide real-time weight updates for the RNN, enabling control over maximum power extraction. According to simulation results, the suggested controller outperforms a traditional control approach in tracking the optimal turbine rotation speed and extracting the most wind power from RATs by 13 times, even in severe nonlinearities and system uncertainties.

关键词： Renewable energy sources Uncertainty Recurrent neural networks Stability analysis Real-time systems Hardware Wind turbines Vehicle dynamics Sliding mode control Wind energy conversion

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Enhancing Traffic Flow Forecasting with Spatio-Temporal Information: A Case Study on Highway Networks in Belgium

Enhancing Traffic Flow Forecasting with Spatio-Temporal Info...

引用

International Conference on instrumentation control and Automation (ICA)

作者： Muhammad Farhan Fathurrahman Arne Catteeuw Sidharta Gautama Angel Lopez Aguirre Endra Joelianto Herman Y. Sutarto Department Of Industrial Systems Engineering and Product Design Ghent University Ghent Belgium Department of Intelligent System PT. Pusat Riset Energi (PRE) Bandung Indonesia FlandersMake@UGent–Corelab ISyE Lommel Belgium Instrumentation and Control Research Group Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia

As the number of vehicles continues to increase every year, it is crucial to monitor traffic conditions effectively. Traffic forecasting serves as a valuable method in traffic management to support decision making. This study investigates the impact of utilizing spatio-temporal data for traffic flow forecasting, as opposed to forecasting each location individually. We compare spatio-temporal Long Short-Term Memory (LSTM), a machine-learning technique that utilizes spatially correlated sensor data in a network, and compare this to conventional LSTM and Seasonal ARIMA (SARIMA). Experiments have been conducted on counting loop data of a highway network in Belgium. We have investigated the performances of the forecasting model for different prediction horizons. The results show that spatial information improves the performance of the forecasting model and reduces the training time required. Further analysis show that the spatio-temporal LSTM improves majorities of detectors while the minorities detectors are degraded which imply the importances of network selection. The computational load of the spatio-temporal LSTM model is minimally impacted by the number of sensors in the network thus making it scalable. The results show that longer prediction horizons degrade the forecasting performance but the impact up to a 12 hour-horizon is not significant.

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