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Variance-Constrained Filtering Fusion for Nonlinear Cyber-Physical Systems With the Denial-of-Service Attacks and Stochastic Communication Protocol

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IEEE/CAA Journal of Automatica Sinica 2022年第6期9卷 978-989页

作者： Hang Geng Zidong Wang Yun Chen Xiaojian Yi Yuhua Cheng IEEE School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China Department of Computer Science Brunel University LondonUxbridgeMiddlesexUB83PHUnited Kingdom Key Laboratory for IoT and Information Fusion Technology of Zhejiang School of AutomationHangzhou Dianzi UniversityHangzhou 310018China School of Mechatronical Engineering Beijing Institute of TechnologyBeijing 100081China

In this paper,a new filtering fusion problem is studied for nonlinear cyber-physical systems under errorvariance constraints and denial-of-service *** prevent data collision and reduce communication cost,the stochastic communication protocol is adopted in the sensor-to-filter channels to regulate the transmission order of *** sensor is allowed to enter the network according to the transmission priority decided by a set of independent and identicallydistributed random *** the defenders’view,the occurrence of the denial-of-service attack is governed by the randomly Bernoulli-distributed *** the local filtering stage,a set of variance-constrained local filters are designed where the upper bounds(on the filtering error covariances)are first acquired and later minimized by appropriately designing filter *** the fusion stage,all local estimates and error covariances are combined to develop a variance-constrained fusion estimator under the federated fusion ***,the performance of the fusion estimator is examined by studying the boundedness of the fused error covariance.A simulation example is finally presented to demonstrate the effectiveness of the proposed fusion estimator.

关键词： Cyber-physical system(CPS) denial-of-service attack stochastic communication protocol(SCP) variance-constrained filtering fusion

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Multi-modal feature fusion for 3D object detection in the production workshop

Multi-modal feature fusion for 3D object detection in the pr...

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作者： Hou, Rui Chen, Guangzhu Han, Yinhe Tang, Zaizuo Ru, Qingjun College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China College of Computer Science and Cyber Security Chengdu University of Technology Chengdu China

3D object detection technology is of great significance to realize intelligent perception and ensure the production safety of a workshop. Existing 3D object detection relies on large-scale, high-quality 3D annotation data and is unsuitable for actual workshop scenes’ perception. This paper proposes a multi-modal feature fusion 3D object detection method (MFF3D) for a production workshop. The design of MFF3D includes the following steps: (1) Improved YOLOv3 attains the 2D prior region of an object, and RGB-D saliency detection obtains the object image pixels in that region. (2) Depth image pixels corresponding to the object are projected to generate the object's frustum point cloud, and a multi-modal feature fusion strategy simplifies the object's frustum point cloud, so as to remove outlier points and reduce the number of point clouds. This can replace the 3D object reasoning process based on deep neural networks;(3) An axis-aligned bounding box algorithm is used to generate the object's 3D bounding box, and principal component analysis algorithm (PCA) is used to calculate the object's pose information. MFF3D is applied in the workshop, and experiments verify the feasibility and detection accuracy. We set up a production workshop object dataset (PWOD) for experimental evaluation. In the case of a small amount of 2D annotation data and no 3D annotation data, experimental results show that when the threshold value of intersection over union of 3D object (IoU3D) is 0.5, the mean average precision value of 3D object (mAP3D) reaches 60.31, and the detection speed reaches 3 FPS. MFF3D does not rely on 3D annotation data and can effectively detect objects of a production workshop. © 2021 Elsevier B.V.

关键词： Object detection

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Customized Touch UI Development for E-Cockpit in Automobile 3

Customized Touch UI Development for E-Cockpit in Automobile

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3rd International Conference on Smart Technologies, Communication and Robotics, STCR 2023

作者： Sivaraj, D. Rathika, P.D. Jayasree, D. Dwarkesh Psg College of Technology Department of Electronics and Communication Engineering Coimbatore India Psg College of Technology Department of Robotics and Automation Engineering Coimbatore India Psg Polytechnic College Department of Electronics and Communication Engineering Coimbatore India Psg College of Technology Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350370867

In recent times, the automotive industry has made significant steps towards digitization by focusing on electronic cockpits (E-Cockpits) to enhance the driving experience, comfort and safety. The incorporation of Touch-Based User Interface (UI) technologies has played a crucial role in revolutionizing Driver-Vehicle interaction [10]. The project of E-Cockpit represents a concept that consolidates various internal car systems onto one unified digital platform, enabling seamless control and access to essential infotainment, safety features, and connectivity services [14]. For the realization of the complete potential of an E-Cockpit, it is important to develop an innovative and User-Friendly touch UI as this directly influences both user experience and safety concerns. © 2023 IEEE.

关键词： User interfaces

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A Switched Capacitor Based Single-Switch Ultrahigh Step-Up DC-DC Converter 7

A Switched Capacitor Based Single-Switch Ultrahigh Step-Up D...

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7th IEEE International Electrical and Energy Conference, CIEEC 2024

作者： Fu, Yu Ren, Zepei Hao, Shicheng Li, Shouxiang Xie, Wenhao School of Automation Beijing Institute of Technology Beijing China School of Computer and Communication Engineering Northeastern University at Qinhuangdao Qinhuangdao China College of Electrical and Electronic Engineering Wenzhou University Wenzhou China

ISBN: (纸本)9798350359558

This paper proposes a switched capacitor based step-up DC-DC converter with the advantages of single-switch, continuously adjustable ultrahigh voltage gain and low input current ripple. To achieve high gain characteristics, the converter utilizes a quadratic boost converter on the input side to ensure continuous input current. Additionally, it implants the second winding of a coupled inductor within it, connecting it to the first winding of the coupled inductor and a voltage multiplier. The analysis includes a discussion of the operating principle, the derivation of the steady-state key equations, the voltage and current stress on the components, and the boundary condition. A functional prototype is built to confirm the theoretical analysis. © 2024 IEEE.

关键词： Boost converter

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Research on Trajectory Tracking of Dielectric Elastomer Based on RBFNN

Research on Trajectory Tracking of Dielectric Elastomer Base...

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2023 IEEE International Conference on Unmanned Systems, ICUS 2023

作者： Guan, Yuanlin Yang, Xixin Wang, Chaolong Chen, Meiyi Xu, Guangsheng Xie, Jing School of Mechanical & Automotive Engineering Qingdao University of Technology Qingdao China School of Automation Qingdao University Qingdao China College of Computer Science & Technology Qingdao University Qingdao China

ISBN: (纸本)9798350316308

Aiming at the problem of nonlinear motion caused by the viscoelasticity and hyperelasticity of dielectric elastomers, in order to realize the linear motion of the actuator structure, this paper proposes a trajectory tracking method of dielectric elastomers based on RBFNN optimal adaptive control. A dielectric elastic body dynamics model based on the Gent model is established to analyze the nonlinear motion performance of the structure. Combining with the problem that it is difficult to obtain the viscoelastic and hyperelastic models of dielectric elastomers, the unknown items in the model are estimated using the method based on radial basis neural network. According to the estimation results of the neural network, a sliding mode controller is designed to realize the tracking control target of the dielectric elastomer, and the influence law of the excitation frequency on the model motion trajectory is researched. Finally, the effectiveness of the proposed control strategy is verified by numerical simulation experiments, and further optimization design and experimental verification are realized. © 2023 IEEE.

关键词： Viscoelasticity

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Lighting the Smart Way: A Technological Odyssey in Urban Street Illumination 10

Lighting the Smart Way: A Technological Odyssey in Urban Str...

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10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Vinu, M.S. Priya, P Kanaga Thilakaveni, P. Hermina, J. M. Ashforn Prashanthini, K. Misba, M. Nehru Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Kpr Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Psg Polytechnic College Department of Computer Engineering Coimbatore India Bannari Amman Institute of Technology Department of Artificial Intelligence and Data Science Erode India Sri Ramakrishna Engineering College Department of Robotics and Automation Coimbatore India Bethlahem Institute of Engineering Department of Computer Science and Engineering Nagercoil Karungal India

ISBN: (纸本)9798350384369

The development of intelligent street light systems has ushered in a new era of efficiency and sustainability in urban infrastructure. The proposed work studies the integration of modern sensors and Internet of Things (IoT) technologies to increase the functionality of street lights. The major components include Light Dependent Resistors (LDR) for automatic light management, an MQ135 sensor for air quality monitoring, and a fog detection system employing a laser module and LDR. These sensors are integrated with the ESP8266, providing cloud integration for real-time data visualization and monitoring. Additionally, solar panels are employed to enhance energy efficiency. The proposed methodology digs into the precise implementation, data analysis, and the potential of this system to alter urban lighting infrastructure © 2024 IEEE.

关键词： Air quality

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PID-F Controlled LFC in a Two-Area Power System with Renewable Integration Using Metaheuristic Approaches

PID-F Controlled LFC in a Two-Area Power System with Renewab...

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2024 IEEE Global Energy Conference, GEC 2024

作者： Can, Özay Izci, Davut Ekinci, Serdar Ghandour, Raymond Salman, Mohammad Department of Electronics and Automation Recep Tayyip Erdogan University Rize Turkey Department of Computer Engineering Batman University Batman Turkey College of Engineering and Technology American University of the Middle East Kuwait

ISBN: (纸本)9798331532611

As a result of the rising usage of renewable energy sources (RES) and the altering load profile, it is becoming increasingly difficult to strike a balance between production and demand. This is because renewable energy sources are becoming more prevalent. For this reason, it is of the utmost importance to put the process of load frequency control (LFC) into action. Taking this into consideration, the objective of this study is to optimize the adjustment of the parameters of the proportional-integral-derivative with filter (PID-F) controller for the LFC process in a two-area power system that consists of photovoltaic (PV) panels and wind energy systems simultaneously. During the past few years, a number of innovative algorithms have been developed. These algorithms include the mountain gazelle optimizer (MGO), the hippopotamus optimizer (HO), and the puma optimizer (PO). The parameters of the PID-F controller were determined with the help of these algorithms, which were applied accordingly. The findings of the simulation reveal that all three algorithms managed to achieve results that were successful and comparable to one another in the LFC process. These results were attained by all three algorithms. ©2024 IEEE.

关键词： Wind power

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A Data-Based Feedback Relearning Algorithm for Uncertain Nonlinear Systems

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IEEE/CAA Journal of Automatica Sinica 2023年第5期10卷 1288-1303页

作者： Chaoxu Mu Yong Zhang Guangbin Cai Ruijun Liu Changyin Sun the School of Electrical and Information Engineering Tianjin UniversityTianjin 300072China the College of Missile Engineering Rocket Force University of EngineeringXi’an 710025China the School of Computer and Information Engineering Beijing Technology and Business UniversityBeijing 100048China the School of Automation Southeast UniversityNanjing 210096China

In this paper,a data-based feedback relearning algorithm is proposed for the robust control problem of uncertain nonlinear *** by the classical on-policy and off-policy algorithms of reinforcement learning,the online feedback relearning(FR)algorithm is developed where the collected data includes the influence of disturbance *** FR algorithm has better adaptability to environmental changes(such as the control channel disturbances)compared with the off-policy algorithm,and has higher computational efficiency and better convergence performance compared with the on-policy *** processing based on experience replay technology is used for great data efficiency and convergence *** experiments are presented to illustrate convergence stability,optimality and algorithmic performance of FR algorithm by comparison.

关键词： Data episodes experience replay neural networks reinforcement learning(RL) uncertain systems

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ToMFIR and Auxiliary Signals based Active Incipient Fault Detection for Autonomous Underwater Vehicle Thrusters 43

ToMFIR and Auxiliary Signals based Active Incipient Fault De...

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43rd Chinese Control Conference, CCC 2024

作者： Zhu, Zefan Wu, Yunkai Zhou, Yang Zhu, Zhiyu Soh, YengChai Jiangsu University of Science and Technology College of Automation Zhenjiang212100 China Jiangsu University of Science and Technology School of Computer Science and Engineering Zhenjiang212100 China Nanyang Technological University School of Electrical and Electronic Engineering Singapore Singapore

ISBN: (纸本)9789887581581

This article proposes an active fault detection method combining the Total Measurable Fault Information Residual (ToMFIR) and auxiliary signals to address the incipient faults of autonomous underwater vehicle (AUV) thrusters. Firstly, the Takagi-Sugeno (T-S) fuzzy medelling of AUV dynamics is establised. Secondly, an auxiliary signal and redundant actuator module are introduced. The auxiliary signal is capable of amplifying the active ToMFIR in the event of a fault, while the redundant actuator ensures that the auxiliary signal does not interfere with the active ToMFIR in fault-free scenarios. Performance indicators and fixed thresholds are provided to assist in designing the parameters of the redundant actuator. This is done by maximizing the impact of the auxiliary signal on ToMFIR signals and minimizing any disturbances. Finally, simulation results demonstrate the effectiveness of the proposed method in improving the sensitivity for incipient faults in AUV propulsion systems. © 2024 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Autonomous underwater vehicles

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Domain Contrastive Learning for Multi-Site Alzheimer's Disease Classification 20

Domain Contrastive Learning for Multi-Site Alzheimer's Disea...

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20th International computer Conference on Wavelet Active Media technology and Information Processing, ICCWAMTIP 2023

作者： Fiasam, Linda Delali Rao, Yunbo Sey, Collins Aggrey, Esther Stacy E. B. Kodjiku, Seth Larweh Browne, Judith Ayekai Danso, Juliana Mantebea Ukwuoma, Chiagoziem C. Gyarteng, Emmanuel S. A. School of Information and Software Engineering University of Electronic Science and Technology of China China School of Computer Science and Technology Zhejiang Gongshang University China School of Computer Science and Technology University of Electronic Science and Technology of China University China College of Nuclear Technology and Automation Engineering Chengdu University of Technology China

ISBN: (纸本)9798350318982

In the field of medical imaging, accurately classifying Alzheimer's Disease (AD) poses a substantial challenge, primarily due to the inherent variability in imaging data across different clinical sites. This paper introduces a novel approach, Domain Contrastive Learning (DCL), to address this challenge by enhancing the robustness and transferability of AD classification models using multi-site Magnetic Resonance Imaging (MRI) data. DCL leverages a unique contrastive learning technique within an autoencoder's latent space, enabling the extraction of domain-invariant features essential for accurate diagnosis. We rigorously evaluate the proposed network on brain images from three distinct imaging sites, employing a Domain Generalization (DG) training protocol to ensure robustness and generalizability across varying data sources. Our model is evaluated on three binary classification tasks: AD vs. Normal Control (NC), AD vs. Mild Cognitive Impairment (MCI), and MCI vs. NC. Results demonstrate that DCL outperforms existing methods, especially in AD vs. NC classification, achieving higher accuracy, sensitivity, and specificity with 0.51%, 1.54% and 1.68% increments respectively. This underscores DCL's potential as a robust and generalizable method for enhanced AD diagnosis, marking a significant step forward in medical imaging challenges in a multi-site context. © 2023 IEEE.

关键词： Magnetic resonance imaging

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