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检索条件"任意字段=13th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2023"

共 285 条记录，以下是151-160 订阅

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Modeling a Single Camera system based on Predicted Bounding Box and Pan-Tilt Angles

Modeling a Single Camera System based on Predicted Bounding ...

引用

ieee international conference on system engineering and Technology

作者： Adi Novitarini Putri Fabiola Maria Egi Hidayat Dimitri Mahayana Carmadi Machbub Control and Computer Research Group School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Institut Teknologi Sains Bandung Bekasi Indonesia

the control schemes that are related to visual servoing systems are often done through trial and error. Based on the classical control concept, it is necessary to have a mathematical model of the plant before designing the controller. therefore, this research focuses on producing a mathematical model of the pan-tilt system. We propose the combination of the computer vision method with the classic system identification method, namely N4SID to obtain the dynamics model of a pan-tilt system. In this research, the system identification procedure was successful in producing a state-space model of a visual servoing system using a pan-tilt system and a single camera. this study merged traditional system identification techniques with computer vision to create a discrete-time linear state-space model. When the system order value equals three, the approximation with the minimum MSE value is obtained.

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A Review of Potential AI-Based Automation for IoT-Enabled Smart Homes

A Review of Potential AI-Based Automation for IoT-Enabled Sm...

引用

ieee international conference on system engineering and Technology

作者： Ying Mei Leong Ean Heng Lim Lip Khi Lim Faculty of Computing and Engineering Quest International University Ipoh Malaysia Faculty of Information and Communication Technology Universiti Tunku Abdul Rahman Ipoh Malaysia School of Computing Newcastle University Newcastle United Kingdom

the Internet of things (IoT) has brought significant changes in the way we interact with technology in our homes. Smart homes equipped with IoT devices offer a comfortable and convenient lifestyle. However, managing these devices and their operations can be challenging, especially for individuals with limited technical expertise. the integration of artificial intelligence (AI) in IoT-based smart homes can potentially overcome these challenges by automating device management and enabling proactive responses to users’ needs. this paper investigates the potential of AI-based automation for IoT-enabled smart homes. We review the literature on AI-based automation and IoT-based smart homes, highlighting their benefits, challenges, and existing solutions. the research methodology used in this study is through deep learning approach. the results indicates that AI-based automation can improve user experience and enhance the efficiency and effectiveness of IoT-based smart homes. However, some technical and ethical challenges, such as privacy and security concerns, need to be addressed.

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A Data Mining Approach to Finding Face Mask from Bangladeshi News Channel 13

A Data Mining Approach to Finding Face Mask from Bangladeshi...

引用

13th international conference on computing Communication and Networking Technologies, ICCCNT 2022

作者： Arman, Md Shohel Alam, Md. Rittique Jahan, Hasnur Islam, Lameya Sammak, Musabbir Hasan Biplob, Khalid Been Md. Badruzzaman Daffodil International University DIU Data Science Lab Department of Software Engineering Dhaka Bangladesh

ISBN: (数字)9781665452625

ISBN: (纸本)9781665452625

Face Mask Detection is currently a hot topic that has piqued the interest of researchers all over the world. Today, the entire world is dealing with the COVID-19 pandemic. To control the spread of the Coronavirus the most important task people need to do is use a mask. there is still a lot of research and study being done on COVID-19. Several studies have also shown that wearing a face mask significantly reduces the problem of viral transmission. In addition, a person wearing a face mask perceives a sense of protection. When we are at home, we take care of everything, but when we are in public places such as offices, malls, and colleges, it becomes more difficult to keep people safe. Machine Learning and Data Mining are a collection of technologies that provide effective solutions to complex problems in a variety of fields. We attempted to develop a face mask recognition system using machine learning in order to prevent the spread of the Coronavirus. this is a good system for detecting a face mask in news channel images and videos. It can recognize both Mask and No Mask faces. With the advancement of this system, it will be possible to detect whether or not a person is wearing a face mask. If the person is not wearing a face mask, it will display a message such as "No Mask,"otherwise it will display "Mask Detected." © 2022 ieee.

关键词： Data mining

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Performance Evaluation of Particle Swarm Optimisation control for Traffic Light systems in Roundabouts

Performance Evaluation of Particle Swarm Optimisation Contro...

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ieee international conference on system engineering and Technology

作者： Benjamin Ooi Joon Ming Richard T.K. Wong Muhammed Basheer Jasser Hui Na Chua Department of Computing and Information Systems Sunway University Sunway City Selangor Malaysia

Although the usage of roundabouts has been widely implemented as an alternative to signalised intersections as a version of traffic control, it is still reported that major traffic congestions commonly occur at roundabouts in urban areas. However, studies show that one of the most promising methods to overcome this issue is through the implementation of an evolutionary algorithm as a method to control the phase timings of the traffic light system at roundabouts. As such, this project aims to evaluate the effectiveness of implementing particle swarm optimisation (PSO) as the traffic light control for a signalised roundabout. Hence the performance of the PSO-controlled signalised roundabout is compared with that of a fixed-time signalised roundabout and also the unsignalised roundabout under different traffic conditions. this project presents a case study inspired by a real-world roundabout, namely the Persiaran Anggerik Mokara Roundabout in Kota Kemuning, Shah Alam, Malaysia. From the study, we can conclude that the usage of a Particle Swarm optimisation (PSO) algorithm is suitable in finding more effective green traffic light phase timings compared to fixed-time traffic lights for all test cases. However, the implementation of the PSO-controlled signalised roundabout is less effective compared to unsignalised roundabouts due the minimal delay incurred from an unsignalised round design. As such, it was concluded that when designing a roundabout system that is of similar characteristics as the modelled roundabout for this project, an unsignalised approach to the roundabout system greatly outperforms any traffic light system that only has traffic signals at the entrances of the roundabout.

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Security of Networked systems with Random Sampling Intervals and Deception Attacks Via Non-Fragile Sampled-Data control

Security of Networked Systems with Random Sampling Intervals...

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ieee international conference on Cyber Technology in Automation, control, and Intelligent systems

作者： Zhipei Hu Chen Wang Jin Zhang Xutao Li An-Min Zou School of Electrical and Information Engineering Shantou University Shantou China School of Mechatronic Engineering and Automation Shanghai University Shanghai China

this study is concerned with the security of networked systems with random sampling intervals and deception attacks using non-fragile sampled-data control. We first establish a discrete-time stochastic model framework for the networked system with random sampling intervals and deception attacks. Subsequently, by the vectorization and Kronecker product operation, a non-fragile controller is designed such that the exponential mean-square stability of resulting discrete-time stochastic system is guaranteed. Finally, a numerical example is presented to show the effectiveness of the designed algorithm.

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Truncated Predictor Feedback control for Linear systems with Multiple Distributed Input Delays

Truncated Predictor Feedback Control for Linear Systems with...

引用

ieee international conference on Cyber Technology in Automation, control, and Intelligent systems

作者： Guangjie Wang Qingsong Liu School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China

this paper aims to deal with the delay compensation problem for linear systems in the presence of three distributed input delays. A fresh state variable is instituted so as to design the state-based feedback controllers. Whereafter, truncated predictor feedback (TPF) approaches are built to make up for the three distributed input delays. It is displayed that the original system possessing three distributed input delays can be stabilized via the TPF controller. Additionally to demonstrating the efficacy of the built controller via an example.

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Adaptive Event-Triggered control for the Nonlinear Cascade systems: A HOFA system Approach

Adaptive Event-Triggered Control for the Nonlinear Cascade S...

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ieee international conference on Cyber Technology in Automation, control, and Intelligent systems

作者： Lou Wang Yu-Xuan Liu Cui-Hua Zhang Chang-Chun Hua Yan-Qiao Wei Institute of Electrical Engineering Yanshan University Qinhuangdao China

For a class of nonlinear cascade systems, a novel method is used to acquire the event-triggered control law. Different from the traditional backstepping method, by the recursive design approach of “ascending order and descending dimension”, the cascade systems are transformed into the high-order fully actuated (HOFA) model. By the HOFA system method, the control law is further obtained. the adaptive controller is designed along with the event-triggered mechanism (ETM) to save the workload and the energy in signal transmission. We prove that for the closed-loop system, all the signals are uniformly bounded at last. A simulation example is presented, which shows the effectiveness of the adaptive event-triggered controller.

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Research on Optimization Strategy of Extinguishing Angle control Function in DC Transmission

Research on Optimization Strategy of Extinguishing Angle Con...

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ieee international conference on Power and Energy systems (ICPES)

作者： Haibin Liu Weipeng Liu Yawei Chang Ke Zhang DC Transmission Branch XJ Electric Corporation Xuchang China

At present, in high-voltage DC transmission systems, when the AC system on the inverter side malfunctions, if the DC control system responds improperly, it will lead to inverter commutation failure. Studying from the principle of extinguishing angle control, the advantages and disadvantages of measurement based and calculation based extinguishing angle control methods were compared. A composite control strategy in DC transmission engineering is proposed, and a corresponding control protection model is established in PSCAD/EMTDC, and the feasibility of the optimization strategy is verified. this strategy can effectively avoid the continuous commutation failure of the converter station caused by ground faults in the system, and improve the stable operation efficiency of the DC system.

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MPPT control of Photovoltaic Power Generation system Based on Improved Eagle Perching Optimization Algorithm

MPPT Control of Photovoltaic Power Generation System Based o...

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ieee international conference on Cyber Technology in Automation, control, and Intelligent systems

作者： Jinzhao Cui Hong Wang Chao Ge Changchun Hua College of Electrical Engineering North China University of Science and Technology Hebei China College of Electrical Engineering Yanshan University Hebei China

Photovoltaic power generation system is susceptible to temperature and light conditions, and its P-V curve shows multiple peaks, which reduces the effectiveness of the traditional maximum power point tracking method. Aiming at this problem, the eagle perching optimization algorithm (EPO) is introduced into maximum power-point-tracking (MPPT) control, and its scaling factor and incremental formula are improved, which effectively improves the convergence speed and reduces the number and amplitude of shocks. In Matlab/Simulink simulation, three test environments are set up: no shadow condition, static shadow condition and abrupt shadow condition. It is verified that the improved eagle perching optimization algorithm can track the maximum output power point of photovoltaic array quickly and stably, and improve the working efficiency of photovoltaic power generation system.

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Fully Distributed Adaptive Finite Time Fault-Tolerant control for Multi-Agent systems with Actuator Faults

Fully Distributed Adaptive Finite Time Fault-Tolerant Contro...

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ieee international conference on Cyber Technology in Automation, control, and Intelligent systems

作者： Xiaoqi Wang Yiming Fang Miao Xu Zhichao Lei Key Labpratory of Industrial Computer Control Engineering Yanshan University Qinhuangdao Hebei Province China Engineering Research Center of the Education Ministry for Intelligent Control System and Intelligent Equipment Yanshan University Qinhuangdao Hebei Province China

For a class of second-order nonlinear leader-following multi-agent systems with actuator faults and integral quadratic constraints (IQCs) of followers, a fully distributed adaptive consensus control algorithm based on improved PID sliding mode is designed. the algorithm only requires local topology information but no global information. According to Lyapunov stability theory, it is demonstrated that multi-agent systems can converge to the vicinity near equilibrium points within a finite time. Finally, the feasibility of the control algorithm proposed in this paper is verified by numerical simulation of multi-agent systems.

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