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17th INDIACom;2023 10th International Conference on Computing for Sustainable Global Development, INDIACom 2023

作者： Ramesh, S.P. Abdulwahid, Ali Hadi Anjum, Afsana Venkatesh, N. Singh, Rajesh Chakravarthi, M. Kalyan Amet University Department of Computer Science and Engineering Tamil Nadu Kanathur India Southern Technical University Engineering Technical College Department of Control and Automation Basra Iraq Jazan University Department of Information Technology and Security Jazan Saudi Arabia School of Computer Science and Artificial Intelligence Sr University Telangana Warangal India Uttaranchal Institute of Technology Uttaranchal University India School of Electronics Engineering VIT-AP University Amaravathi India

ISBN: (纸本)9789380544472

The demand on healthcare is growing as a result of the expanding global population, rising demands for successful treatment, and an underlying improvement in life quality. Consequently, healthcare remains one of the most significant social and economic problems in the world, necessitating the development of new and more sophisticated scientific and technological treatments.E-health services are provided via personalised healthcare systems to meet the medical and support needs of the ageing population. An important development in the Big Data age is the Internet of Things, which facilitates several real-time engineering solutions through improved services. Healthcare systems are now using analytics over IoT data streams as a stream of user data to find new information, forecast rapid recognition, and make decisions on life-threatening situations. In this study, researchers have carried out a thorough review of the hottest recent revolutionary technologies in bespoke healthcare systems, with a focus on hypervisor, cloud infrastructure, big data analytic, the Web of Things, and smartphone apps. In order to make early disease detection and diagnosis possible, it is important to develop a better healthcare system. We have examined these problems and suggested potential solutions while offering secure e-health services. The purpose of this study is to design a smart and secure remote monitoring and warning system using the latest emerging technologies in 21stcentury such as big data analytics and Internet of Things (IoT) ecosystems. In this study the researchers discussed a detailed research methodology to meet the outcomes of the reerach. All the relevant findings and analysis are explained in descriptive manner. Moreover, this study highlights the constantly expanding requirements for better medical systems in the present and offers potential directions for future research. © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Internet of things

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A Survey on Pipeline Magnetic Flux Leakage Inspection Data Processing Technology 2

A Survey on Pipeline Magnetic Flux Leakage Inspection Data P...

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2nd International Conference on Artificial Intelligence, automation, and High-Performance Computing, AIAHPC 2022

作者： Dongsheng, Zhao Lijian, Yang Yiran, Liu Hao, Geng Sen, Wang School of Information Science and Engineering Shenyang University of Technology Liaoning Shenyang110870 China PipeChina Oil&Gas Control Center Beijing100013 China College of Automation Shenyang Institute of Engineering Shenyang110136 China

ISBN: (纸本)9781510657717

Pipeline Magnetic Flux Leakage (MFL) inspection data processing is a necessary part of the pipeline internal detection tasks, which results are the bases of excavation and maintenance. At present, pipeline construction is increasing rapidly. Thus, pipeline inspection and maintenance work will increase year by year. In order to improve the work efficiency and quality, detection data processing should be done automatically or intelligently by computer instead of artificial way. Considering that MFL detection is still the mainstream of long-distance oil and gas pipeline inspection method, some processing technology for MFL data, such as pre-processing, data visualization, MFL image recognition and defect qualification, etc., is summarized, and its difficulties and hotspots are discussed. © 2022 SPIE. All rights reserved.

关键词： Data visualization

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Spectrum Sensing for Cognitive Radio Based on Feature Extraction and Deep Learning 11

Spectrum Sensing for Cognitive Radio Based on Feature Extrac...

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2022 11th International Conference on Information and Electronics engineering, ICIEE 2022

作者： Geng, Yue Huang, Jingyi Yang, Jianxin Zhang, Sen School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518061 China School of Mechanical Engineering & Automation Beihang University Beijing100191 China School of Measurement-Control and Communication Engineering Harbin University of Science and Technology Harbin150080 China

In cognitive radio, spectrum sensing is used to determine whether the primary user is using the spectrum based on the signal received on a specific frequency band, thereby determining whether the secondary user can use the spectrum. The main problem faced by spectrum sensing is how to identify the existence of the primary signal under the condition of low signal-to-noise ratio (SNR). Compared with traditional technologies, deep learning methods can identify the features of input data more efficiently and accurately. Based on convolutional neural network (CNN), This paper regard spectrum sensing as a binary classification problem. In the method we proposed, different features of received are extracted, and a dataset of feature matrices obtained under different SNRs is constructed for the training of the CNN network. Experiment results show that under the condition of low signal-to-noise ratio, the performance of our method is improved compared with the traditional method, and the combination of different features can improve the sensing accuracy. © Published under licence by IOP Publishing Ltd.

关键词： Cognitive radio

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An Iterative Mode Merging Method For Multimode Process Monitoring With Transition Mode

An Iterative Mode Merging Method For Multimode Process Monit...

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Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS), CAA Symposium on

作者： Yu Lin Cong Zhang Sihang Zhang Yiming Wan School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Beijing Insitute of Control Engineering Beijing China

An industrial process typically consists of multiple production modes, and transitions between two modes often cause difficulties for process monitoring. For the transitions between steady-state modes, it is common to ignore or combine them with other modes for modeling. The former is likely to cause false alarms, and the latter reduces the detection rate of the monitoring process. Efficient and accurate demarcation of the transition mode from the steady mode presents an intriguing research topic. To address this issue, this paper presents an innovative iterative mode merging approach for multimode process monitoring with transition mode. The data is segmented according to the proportion of principal components to the total space, and then iterative mode merging (the merging of data of the same mode) is performed according to the reconstruction error of the probabilistic principal component analysis (PPCA) model. A case study using a multiphase flow dataset demonstrates the effectiveness of the proposed method.

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Triggered Mechanism for Strict Feedback Systems Under Unknown control Directions

Triggered Mechanism for Strict Feedback Systems Under Unknow...

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Asian control Conference

作者： Guilong Liu Hongda Wu Yongliang Yang Wei Xie Weidong Zhang School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

This paper presents an event-based asymptotic tracking control scheme designed for strict feedback systems with unknown control directions. The control directions directly determine how the controller acts on the system, thus impacting the system's stability and convergence speed. When the control directions are unknown, it presents a significant challenge in controller design. To tackle this issue, the Nussbaum-type gains are introduced. However, this method increases communication overhead. Hence, an event-triggered mechanism is introduced to alleviate this burden. Additionally, to achieve and maintain desired target states, satisfying control requirements and performance demands, this paper improves the event-triggered mechanism to achieve asymptotic tracking. Finally, the feasibility and effectiveness of the proposed design are validated through a simulation example.

关键词： Asymptotic stability Target tracking Stability criteria control systems Optimization Convergence

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Event-Triggered Output Voltage Practical Tracking control for Uninterruptible Power Supply Systems

Event-Triggered Output Voltage Practical Tracking Control fo...

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第35届中国控制与决策会议

作者： Ben Wu Wei Liu Weijie Sun Key Laboratory of Autonomous Systems and Networked Control Ministry of EducationSchool of Automation Science and EngineeringSouth China University of Technology

In this paper,by using the output regulation theory,we research the output voltage practical tracking problem for uninterruptible power supply systems under event-triggered control *** configuring the desired poles for a controllable pair and solving the regulator equations,a state feedback gain and a feedforward gain can be obtained for designing the control ***,under event-triggered mechanism,a control law that can be applied to a digital platform directly is designed to solve our ***,it can be verified that the voltage tracking error can converge to a pre-specified neighborhood of the origin.

关键词： Uninterruptible power supply output regulation event-triggered control

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ADRC Combined with IMC for Non-Minimum Phase Systems

ADRC Combined with IMC for Non-Minimum Phase Systems

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第42届中国控制会议

作者： Xiangyang Li Xindi Deng Senping Tian Wei Ai Key Laboratory of Autonomous Systems and Network Control Ministry of EducationSchool of Automation Science and EngineeringSouth China University of Technology

The integrated control method,active disturbance rejection control(ADRC) combined with internal model control(IMC),is proposed for non-minimum phase *** ADRC combined with IMC is to reduce the influence of zeros on right half plant(RHP),system uncertainty and outer *** improved IMC is put in the inner loop and ADRC is adopted in the outer *** order to enhance the system's stability,an approximate zero phase error model of controlled plant(ZPEM) is used as the internal model in the IMC control loop where the feedback of the inner loop is the dynamic weighted filter sum of the real output and the ZPEM *** theoretical analysis and simulations verify effectiveness of the proposed method for non-minimum phase systems.

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Temperature Gradient Analyses of a Tubular Solid Oxide Fuel Cell Fueled by Methanol

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Transactions of Tianjin University 2023年第1期29卷 14-30页

作者： Qidong Xu Meiting Guo Lingchao Xia Zheng Li Qijiao He Dongqi Zhao Keqing Zheng Meng Ni Department of Building and Real Estate Research Institute for Sustainable Urban Development(RISUD)&Research Institute for Smart Energy(RISE)The Hong Kong Polytechnic UniversityHong Kong 999077China School of Artifi cial Intelligence and Automation Key Laboratory of Image Processing and Intelligent ControlHuazhong University of Science and TechnologyWuhan 430074China School of Low-Carbon Energy and Power Engineering China University of Mining and TechnologyXuzhou 221116China

Thermal management in solid oxide fuel cells(SOFC)is a critical issue due to non-uniform electrochemical reactions and convective fl ows within the ***,a 2D mathematical model is established herein to investigate the thermal responses of a tubular methanol-fueled *** show that unlike the low-temperature condition of 873 K,where the peak temperature gradient occurs at the cell center,it appears near the fuel inlet at 1073 K because of the rapid temperature rise induced by the elevated current *** the large heat convection capacity,excessive air could not eff ectively eliminate the harmful temperature gradient caused by the large current ***,optimal control of the current density by properly selecting the operating potential could generate a local thermal neutral ***,the maximum axial temperature gradient could be reduced by about 18%at 973 K and 20%at 1073 K when the air with a 5 K higher temperature is ***,despite the higher electrochemical performance observed,the cell with a counter-fl ow arrange-ment featured by a larger hot area and higher maximum temperature gradients is not preferable for a ceramic SOFC system considering thermal ***,this study could provide insightful thermal information for the operating condition selection,structure design,and stability assessment of realistic SOFCs combined with their internal reforming process.

关键词： Solid oxide fuel cell Modeling Methanol fuel Temperature gradient Internal reforming

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Multi Classification Online Monitoring of Photovoltaic Array Fault Diagnosis Algorithm

Multi Classification Online Monitoring of Photovoltaic Array...

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Chinese automation Congress (CAC)

作者： Liming Liu Lingtong Kang Xiuchang Deng Meilin Zheng Jing Liu Weimina Shao School of Electrical Engineering and Automation Xiamen University of Technology Xiamen China School of Nuclear Science and Technology University of South China Hengyang China Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control School of Electrical Engineering and Automation Xiamen University of Technology Xiamen China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

With the rapid development of photovoltaic power generation, the fault of photovoltaic array is receiving increasing attention. In response to this issue, proposes an online monitoring photovoltaic array fault diagnosis algorithm based on Support Vector Machines. Firstly, collect the voltage and current of the photovoltaic array for feature extraction. Next, the extracted feature data is normalized and input into a SVM to train the classifier and identify and judge the faults that occur. In the experiment, simulation datasets were used for testing, and online detection and verification were conducted on the real datasets generated by the actual prototype. The results showed that this method can effectively diagnose photovoltaic array faults, with high accuracy and reliability. The online detection photovoltaic array fault diagnosis method based on support vector machine proposed in this paper has high fault detection rate and accuracy, which can provide technical support and guarantee for the maintenance and management of photovoltaic power generation system.

关键词： Photovoltaic systems Fault diagnosis Support vector machines Accuracy Fault detection Feature extraction Classification algorithms Maintenance Arrays Monitoring

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Distributed Resource Allocation via Accelerated Saddle Point Dynamics

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IEEE/CAA Journal of Automatica Sinica 2021年第9期8卷 1588-1599页

作者： Wen-Ting Lin Yan-Wu Wang Chaojie Li Xinghuo Yu School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074 Key Laboratory of Image Processing and Intelligent Control Ministry of EducationHuazhong University of Science and TechnologyWuhan 430074China School of Electrical Engineering and Telecommunications University of New South WalesSydney NSW 2052Australia School of Engineering Royal Melbourne Institute of Technology(RMIT University)Melbourne VIC 3000Australia

In this paper,accelerated saddle point dynamics is proposed for distributed resource allocation over a multi-agent network,which enables a hyper-exponential convergence ***,an inertial fast-slow dynamical system with vanishing damping is introduced,based on which the distributed saddle point algorithm is *** dual variables are updated in two time scales,i.e.,the fast manifold and the slow *** the fast manifold,the consensus of the Lagrangian multipliers and the tracking of the constraints are pursued by the consensus *** the slow manifold,the updating of the Lagrangian multipliers is accelerated by inertial ***-exponential stability is defined to characterize a faster convergence of our proposed algorithm in comparison with conventional primal-dual algorithms for distributed resource *** simulation of the application in the energy dispatch problem verifies the result,which demonstrates the fast convergence of the proposed saddle point dynamics.

关键词： Accelerated saddle point dynamic distributed resource allocation hyper-exponential stability power dispatch

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