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检索条件"任意字段=IEEE International Conference on Cyber Technology in Automation,Control,and Intelligent Systems"

共 35064 条记录，以下是4931-4940 订阅

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DOA Estimation for RIS Assisted Multi-User Wireless Communication System with Squared-Sine Error Criterion and Lawson Norm Constraint 6

DOA Estimation for RIS Assisted Multi-User Wireless Communic...

引用

6th ieee international conference on Electronic Information and Communication technology, ICEICT 2023

作者： Yu, Canping Li, Li Li, Yingsong Sun, Dazhi Li, Liping Huang, Zhixiang Loh, Tian Hong Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China Beijing101399 China National Physical Laboratory Electromagnetic and Eletrochemical Technologies Department Middlesex Teddington United Kingdom

ISBN: (纸本)9798350399059

Reconfigurable intelligent surface (RIS) can control the phase of reflected signals, and has become a hotspot in the field of wireless communication. In this paper, we propose a direction-of-arrival (DOA) estimation algorithm for RIS assisted multi-user wireless communication systems with squared-sine error criterion and Lawson norm constraint. This algorithm utilizes the sparsity of the signal and can achieve fast and accurate DOA estimation under the interference of impulsive noises. To suppress the line-of-sight (LOS) interference and thus to maximize the received signal-to-interference-plus-noise ratio (SINR), we also propose a random optimal phase selection (ROPS) technique to design the control matrix of RIS elements. The simulation results show that the proposed algorithm performs better than the existing methods. © 2023 ieee.

关键词： Impulse noise

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Analysis of the impact of vehicle-to-grid V2G as a distributed generation in the Smart Grid 1

Analysis of the impact of vehicle-to-grid V2G as a distribut...

引用

1st ieee Colombian Caribbean conference, C3 2023

作者： Campo, S.M. Valdez, L.C. Rozo, L.R. Munoz, P.M. Universidad Cooperativa de Colombia Corporación Universitaria Minuto de Dios Uniminuto Santa Marta Colombia Fundación Universitaria Antonio de Arévalo - Unitecnar Laccei United States Universidad Del Magdalena Universidad Cooperativa de Colombia Santa Marta Colombia Universidad Cooperativa de Colombia Universidad Del Magdalena Santa Marta Colombia Cartagena Colombia

ISBN: (纸本)9798350341799

The foreseeable expansion of Distributed Generation (DG) and the possibility of a large number of electric vehicles will have a significant impact on the operation, control and management of demand in the current distribution system. The Smart Grid will become more active and efficient. New intelligent algorithms are needed to ensure an adequate interface between the DG and the electricity system (cyber-Physical systems - CPS). In addition, the storage capacity of electric vehicles (V2G) can be used to improve the performance of existing electricity grids, provided they are able to deal with aspects such as energy flow control, massive and simultaneous recharging, the quality of the electricity supply, among others. More than a great technical challenge, this is a great opportunity to evolve the smart grid concept, integrating smart metering with commercial processes and, at the same time, allowing flexible operation at all distribution levels, increasing efficiency and quality of service, postponing investments to reinforce the network, while reducing investment and operating costs. The aim of this document is to present this network configuration, its main features and the limitations that this technology presents for its use in today's electricity networks. © 2023 ieee.

关键词： cyber Physical System

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Ground Mobile Robot Traversable Area Recognition Based on 3D CNN and Attention Mechanism

Ground Mobile Robot Traversable Area Recognition Based on 3D...

引用

2023 ieee international conference on Unmanned systems, ICUS 2023

作者： Zhang, Qi Shao, Shiliang Wang, Ting Cao, Zonghan Xu, Fuli Shi, Xianyu School of Software Shenyang University of Technology Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China School of Artificial Intelligence Shenyang University of Technology Shenyang China

ISBN: (纸本)9798350316308

As robot technology advances, ground mobile robots have been widely used in dangerous operation environments such as search, rescue, and bomb disposal. The generation of accurate and reliable traversable area maps is crucial for the autonomous navigation of ground mobile robots, especially in rough, uneven, and complex environments. To acquire a more accurate robot traversable area, this paper presents a traversable area identification method based on 3D convolution and attention mechanism. This method uses the 3D LiDAR point cloud information obtained by laser radar scanning. Firstly, it voxelizes the point cloud to improve the identification efficiency. Then, it optimizes the sparse Bird's Eye View Network to identify the voxelized point cloud. A residual module is introduced between the sub-manifold convolution layer and sparse convolution layer of the 3D sparse convolution to solve the training difficulty caused by network depth. In addition, an attention mechanism module is added to the end of point cloud feature extraction to allow the network to pay more attention to useful information in the features. Experimental results show that our network can achieve superior identification results compared to the Bird's Eye View Network. © 2023 ieee.

关键词： Convolution

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Predictive Fault-Tolerant control with Robust Dynamic Output Feedback for Discrete Uncertain systems with Time Delays

Predictive Fault-Tolerant Control with Robust Dynamic Output...

引用

2023 international Annual conference on Complex systems and intelligent Science, CSIS-IAC 2023

作者： Wang, Shiqi Li, Hui Li, Hua Shi, Huiyuan Sun, Qiubai Li, Ping School of Electronic and Information Engineering University of Science and Technology Liaoning Anshan China School of Business Administration University of Science and Technology Liaoning Anshan China School of Information and Control Engineering Liaoning Petrochemical University Fushun China

ISBN: (纸本)9798350309003

In response to discrete industrial processes characterized by unmeasurable states, actuator faults, and time delays, a novel robust predictive fault-tolerant control approach based on dynamic output feedback is proposed. First, we establish an innovative iterative error model that expands the notion of output tracking error to guarantee superior tracking performance for the system. Subsequently, based on the dynamic output feedback method, a robust predictive fault-tolerant controller is developed utilizing this model. By employing Lyapunov stability theory, linear matrix inequality (LMI) techniques, relaxation strategies, and variable transformation methods, stability conditions are given in the form of LMI. Real-time optimal control gains are obtained by online solving of these stability conditions, leading to a significant enhancement in control performance. The feasibility and effectiveness of the proposed approach are finally demonstrated through a simulation case study involving the TTS20 water tank. © 2023 ieee.

关键词： Linear matrix inequalities

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Model-based Robust control of Permanent Magnet Synchronous Motor for Joint Module of Cooperative Robot 8

Model-based Robust Control of Permanent Magnet Synchronous M...

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8th ieee international conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Wang, Zheng Zhen, Shengchao Liu, Xiaoli Chen, Ke Chen, Ye-Hwa School of Mechanical Engineering Hefei University of Technology Anhui Hefei230009 China School of Artificial Intelligence Anhui University Anhui Hefei230601 China The Geroge W.Woodrufi School of Mechanical Engineering Georgia Institute of Technology AtlantaGA30332 United States Anhui University Engineering Research Center of Autonomous Unmanned System and Intelligent Technology Ministry of Education Anhui Hefei230601 China Anhui University Anhui Provincial Engineering Research Center for Unmanned System and Intelligent Technology Anhui Hefei230601 China

ISBN: (纸本)9798350300178

In this paper, a new robust control algorithm is proposed to reduce the influence of load and system parameter changes on the dynamic performance of permanent magnet synchronous motor(PMSM), and finally solve the dynamic control problem of PMSM position tracking. The algorithm's controller is divided into two parts: a nominal control element created using the dynamics model with the goal of stabilizing the nominal motor system;and a robust control element built using the Lyapunov method with the goal of reducing the impact of uncertain factors like nonlinear friction, parameter uncertainty, and outside interference on tracking performance. By means of Lyapunov minimax method, the uniformly bounded and uniformly final bounded systems are proved and the corresponding conclusions are *** on the test platform of permanent magnet synchronous motor, this paper uses cSPACE fast controller to do simulation research. The simulation findings demonstrate that the designed controller is capable of achieving more precise position tracking in the presence of ambiguity as well as good control of the permanent magnet synchronous motor. © 2023 ieee.

关键词： controllers

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Harnessing Machine Learning for Early Detection of Alzheimer's Disease 3

Harnessing Machine Learning for Early Detection of Alzheimer...

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3rd international conference on Communication, control, and intelligent systems, CCIS 2024

作者： Tyagi, Ankita Jhingran, Eashita Singh, Bhupendra Amity University Amity School of Engineering and Technology Uttar Pradesh Noida India

ISBN: (纸本)9798331528201

Alzheimer's Disease (AD) is a degenerative neurological condition that results in the deterioration of cognitive function. Early non-invasive detection is crucial for implementing timely interventions and slowing disease progression. In this research, we aimed to analyse the predictivity for classifying AD stages by integrating neuroimaging data - diffusion tensor imaging (DTI) and structural MRI (sMRI) - with clinical biomarkers. In this paper Fractional Anisotropy (FA) scans, derived from DTI, denoting water molecule diffusion in brain tissue was assessed, particularly in identifying early microstructural changes during the mild cognitive impairment (MCI) stage of AD. To progressively monitor the structural pathology of AD in patients, OASIS sMRI dataset was used. Convolutional neural networks (CNNs) like ResNet 3D and LeNET were applied to analyse FA and sMRI data, achieving a significant accuracy score. In this proposed work, correlation and permutation analysis was also applied on the blood biomarker data to extract relevant features. Random Forest classifier was then used on these biomarkers. The highly correlated biomarkers were later used to obtain a significant impact in identifying the various stages of Alzheimer's progression. © 2024 ieee.

关键词： Diffusion tensor imaging

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intelligent video surveillance with edge-cloud collaboration based on scheduling policy 3

Intelligent video surveillance with edge-cloud collaboration...

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3rd international conference on Consumer Electronics and Computer Engineering, ICCECE 2023

作者： Gong, Chenyu Shandong University of Science and Technology College of Intelligent Equipment Taian China

ISBN: (纸本)9798350331578

With the continuous development of network and communication technology, edge-cloud collaboration can combine the advantages of cloud computing and edge computing to provide efficient safety monitoring services for factories. How to realize efficient edge-cloud collaborative computing for security monitoring is an urgent problem. To this end, this paper proposes a video redundant frame elimination mechanism to images with higher possibility of abnormal events and reduce the system computation overhead;designs a difference threshold-based edge-cloud collaborative scheduling strategy to automatically control the number of image at the edge and cloud according to the difference threshold parameter;designs an edge server intelligent scheduling strategy to assign images to the optimal edge server for processing, thus reducing image queuing time. Simulation results show that the scheduling strategy proposed in this paper can effectively reduce the processing delay and improve the efficiency of edge-cloud collaboration for security surveillance. © 2023 ieee.

关键词： Security systems

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Towards the Design of an intelligent automation Framework for Business Processes 5

Towards the Design of an Intelligent Automation Framework fo...

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5th international conference on Information and Computer Technologies, ICICT 2022

作者： Williams, Olatorera C. Olajide, Funminiyi Nottingham Trent University Department of Computer Science Nottingham United Kingdom

ISBN: (数字)9781665469609

ISBN: (纸本)9781665469609

The impact of emerging technology on organisations has caused technological disruption to business processes. It is therefore required to develop better measures to improve and speed up processes for performance and competitive purposes. intelligent automation is an emerging technological concept that focuses on organisational workflow via the integration of Artificial Intelligence and Machine Learning, for effective operability and decision-making processes. Focusing on business process adaptability, this study aims at proposing a framework for intelligent automation systems. Outcomes could enable adoption, integration, and deployment of intelligent automation to business processes in dynamic environments. © 2022 ieee.

关键词： Decision making

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Artificial Intelligence based Anomaly detection in Distributed energy resources for Smart Grid

Artificial Intelligence based Anomaly detection in Distribut...

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2025 ieee international Students' conference on Electrical, Electronics and Computer Science, SCEECS 2025

作者： Umathe, Shradha Dudhe, Neelima Hiware, Rutuja Vaidya, Prajakta G H Raisoni College of Engineering Department of Electrical Engineering Nagpur India

ISBN: (纸本)9798331529833

The rapid emergence and evolution of Information and Communication Technologies (ICT) has greatly impacted the energy distribution industry. This has led to the transformation of the traditional distribution system into a smart grid. Although the design strategies for smart grids have been studied by academic researchers, there is currently no practical guidance available for the industry on how to improve the level of intelligence in the grid. An industrial control system (ICS) is a type of device that monitors and controls the activities of an industrial environment. Unlike other forms of communication, the traffic of ICS is stable, regular, and periodical. Through statistical modeling, we can analyze the various features of this communication to create a statistical profile of its performance. For instance, by observing the inter-arrival and packet direction of this communication, we can identify the distribution of features that are useful in analyzing the communication. Due to the complexity of the issue, many researchers are currently working on developing techniques to detect anomalous intrusions in smart grids. Unfortunately, there is not enough experience in this field to develop effective approaches. Another issue that emerges when implementing pattern recognition techniques is that it can be very challenging to identify the signals. Due to the nature of the data in smart grids, there are often high levels of misclassification. The ability to detect and prevent power outages is very important for the safety and operation of the power grid. Modern technologies have evolved to provide a large and complex cyber physical system (CPS) that can monitor and control the various components of the power grid. The power grid is continuously improving due to the advancements in technology, and the number of sensors and measurement devices that can be used to monitor and control the system will increase. Unfortunately, this increase in data can overwhelm the existing S

关键词： SCADA systems

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AMPC-ASO Strategy for Nonlinear systems with Uncertainty

AMPC-ASO Strategy for Nonlinear Systems with Uncertainty

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international conference on control and automation (ICCA)

作者： Xiangdan Zhao Lihua Dou Yulong Ding Bin He Biao Wang Zhipeng Wang Yanmin ZhOU Shuo Jiang Yongkang Jiang Gang Li Xiaoqin Liu Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education School of Automation Beijing Institute of Technology Beijing China College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing Jiangsu China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

This paper proposes a control strategy for solving the trajectory tracking control problem with uncertainty in nonlinear systems. Considering the uncertainties and state estimation of the system, an adaptive state observer (ASO) is proposed to solve the estimated problem and ensure the model is adaptive. ASO allows nonlinear systems to be theoretically modelled as linear systems with estimated parameters. Moreover, to satisfy the constraint of adaptive MPC (AMPC) for trajectory tracking control, a parameter identification method for chance-constrained optimization is proposed and uses prediction parameters to compensate for the system's uncertainty by interval estimation and parameter optimization with chance constraints. Finally, the proposed scheme is verified by a quadrotor attitude control simulation. The simulation results show that the AMPC-ASO strategy has perfect tracking control performance.

关键词： Adaptation models Uncertainty Adaptive systems Parameter estimation Trajectory tracking Simulation Predictive models

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