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5th International Conference on Electrical, control and Instrumentation engineering, ICECIE 2023

作者： Oya, Hidetoshi Nakagawa, Takuya Nagai, Shunya Nakano, Kazushi Tokyo City University Department of Computer Science Tokyo Japan Tokyo City University Graduate School of Integrative Science and Engineering Tokyo Japan Niihama College Department of Electronics and Control Engineering Ehime Japan The University of Electro-Communications Graduate School of Informatics and Engineering Tokyo Japan

ISBN: (纸本)9798350325041

This paper proposes a non-iterative LMI-based design strategy for guaranteed cost static output feedback controllers for linear systems. The proposed design approach is based on the well-known necessary and sufficient condition for the existence of the static output feedback stabilizing control for linear systems. In this paper, for linear systems we show the non-iterative LMI-based design procedure for static output feedback controllers which minimize the upper bound of a given quadratic cost function, and the effectiveness of the proposed static output feedback controller with guaranteed cost is presented through a simple numerical example. © 2023 IEEE.

关键词： Linear systems

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Rapid detection model of water pollution based on back propagation neural network

Rapid detection model of water pollution based on back propa...

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2021 International Conference of Social Computing and Digital Economy, ICSCDE 2021

作者： Jin, Tao Zhang, Jian-Fei Wei, Lian-Suo Li, Da-Hui Di, W.U. College of Computer Science and Technology Harbin Engineering University Harbin150001 China College of Computer and Control Engineering Qiqihar University Qiqihar161006 China

ISBN: (纸本)9781665401425

By carrying out the present situation analysis and risk prediction of high mineral groundwater pollution in water source protection areas, it can effectively prevent and control the deterioration of groundwater environment and protect the safety of groundwater resources in water source protection areas. It has certain guiding significance for the development and utilization of local water resources. In this paper, a fast detection model of water pollution based on back propagation neural network is proposed. Combined with the hydrogeological conditions of a water source protection area, a three-dimensional flow system for fast detection of water pollution is established, and the dynamic parameters of fast detection of water pollution are analyzed according to the groundwater flow model. The rationality of the fast detection model and parameter selection are verified by comparing the actual observation values with simulation calculations. In this paper, the back propagation neural network identification method is used to realize the classification and identification of water pollution rapid detection. under certain prediction conditions, Visual Modflow software is used to predict the migration of high-mineral groundwater pollutants in groundwater source protection area within 20 years, which provides relevant basis for the formulation of prevention and control measures of high-mineral groundwater pollution in this water source protection area. Combined with the characteristics of water source protection areas, ammonia nitrogen and chemical oxygen demand (COD) were selected as simulation factors to realize rapid detection of water pollution. The test results show that the accuracy of rapid detection of water pollution by this method is high, and the ability of prediction and quantitative detection of water pollution is improved. © 2021 IEEE.

关键词： Neural networks

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An Adaptive Attitude controller for A Quadrotor Transporting the Payload With Unknown Mass 38

An Adaptive Attitude Controller for A Quadrotor Transporting...

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38th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2023

作者： Qiu, Shihao Chen, Longlong Li, Shuang Lv, Zongyang Tang, Huayi Dalian University of Technology School of Computer Science and Technology Dalian China Dalian University of Technology School of Control Science and Engineering Dalian China Henan University of Technology College of Information Science and Engineering Zhengzhou China Dalian University of Technology School of Mechanical Engineering Dalian China

ISBN: (纸本)9798350303636

An adaptive control approach is presented in this article to deal with the impacts of carrying a payload with unknown mass by a quadrotor. This approach can effectively control the quadrotor's attitude stability. The paper commences by presenting the dynamic model of the quadrotor, followed by the development of a controller to manage its attitude control. Through Lyapunov analysis, the stability of the controller is validated. Ultimately, the proposed controller and a backstepping controller are used to controlling the attitude of the quadrotor, respectively, and experimental outcomes substantiate the efficiency and feasibility of the introduced controller. © 2023 IEEE.

关键词： Adaptive control Quadrotor Unmanned Aerial Vehicle Unknown Mass Payload

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Federated-Boosting: A Distributed and Dynamic Boosting-Powered Cyber-Attack Detection Scheme for Security and Privacy of Consumer IoT

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IEEE Transactions on Consumer Electronics 2024年

作者： Khan, Izhar Ahmed Pi, Dechang Kamal, Shaharyar Alsuhaibani, Mohammed Alshammari, Bandar Mzel Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing China University of Chile Department of Electrical Engineering Chile Qassim University College of Computer Department of Computer Science Buraydah Saudi Arabia Technology Control Company Riyadh Saudi Arabia

Consumer Internet of Things (CIoT) is an emerging technology that took the traditional consumer electronics to next level with smarter devices and higher connectivity. However, the rapid boom of this technology has captured a great deal of hacker's attention in the past decade. Due to resource restricted nature of CIoT devices and limited computational abilities, security professionals are unable to strengthen the security and privacy measures. Since the existing security methods suffers from data imbalance and overfitting issues, this paper proposes a distributed and dynamic weighted boosting method named Federated-Boosting for the accurate and timely detection of cyber-Attacks in CIoT. Specifically, a weighting strategy is designed to overcome the data imbalance issue by dynamically adjusting the weights of weaker class samples. Additionally, a regularized loss function is designed that helps in controlling the overfitting of the model and provide enhance performance and generalization. Finally, a time-based and performance-based dynamic aggregation scheme is designed using distributed training model that keeps the privacy of the CIoT devices intact to the local server. Extensive experiments on two real-world datasets validates the superior performance of Federated-Boosting model against state-of-The-Art detection models. © 1975-2011 IEEE.

关键词： Network intrusion

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A Consumer Electronics-Enhanced UAV System for Agricultural Farm Tracking With Fuzzy SMO and Actuator Fault Detection control Algorithms

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IEEE Transactions on Consumer Electronics 2025年

作者： Bilal, Hazrat Aslam, Muhammad Shamrooz Tian, Yibin Ullah, Inam Ayouni, Sarra Vasilakos, Athanasios V. College of Mechatronics and Control Engineering College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China China University of Mining and Technology Artificial Intelligence Research Institute Xuzhou2211106 China Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China Gachon University Department of Computer Engineering Seongnam13120 Korea Republic of Tashkent State University of Economics Department of Artificial Intelligence Tashkent100066 Uzbekistan Princess Nourah bint Abdulrahman University Department of Information Systems College of Computer and Information Sciences Saudi Arabia Grimstad Norway

The adoption of agricultural robots, or agrobots, has revolutionized modern farming operations, ranging from crop monitoring to automated harvesting, significantly boosting productivity. Motivated by the rapid advancements in agrobots and their integration into smart agricultural practices, this study proposes an autonomous trajectory tracking system for wheat farms using quadcopter UAVs. To address actuator fault detection, including stuck faults and partial loss of efficiency, a TSF-H∞-SMO (Takagi-Sugeno Fuzzy-based H∞ Sliding Mode Observer) fault detection framework is introduced. The approach initiates with the derivation of a TSF (Takagi-Sugeno Fuzzy) attitude control model that integrates an uncertainty term, constructed from the original nonlinear dynamics of the UAV and approximated through local linear models at four equilibrium positions. An actuator fault model is subsequently integrated to develop a comprehensive TSF-UAV model, accounting for actuator faults. The TSF-H∞-SMO is then designed using matrix coordinate transformation to enable precise fault detection. The fault detection capabilities of the TSF-H∞-SMO are evaluated through simulations on the TSF-UAV model under SISO (single-input single-output) actuator fault scenarios. The experimental results validate the proposed system, demonstrating its ability to detect a range of actuator faults accurately and promptly. The analysis reveals a proportional relationship between the amplitude of the state change and the severity of the fault, attributed to the interaction between system states and actuator flaps. This approach underscores the potential for deploying autonomous UAV-based fault detection and trajectory tracking systems in agricultural applications. Furthermore, integrating such advanced fault-tolerant control algorithms holds promise for consumer technology applications, where precision, reliability, and robustness are critical to enhancing system performance and operational efficiency. © 1

关键词： Agricultural robots

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A Novel Hybrid DC Circuit Breaker Topology with Current Limiting Capability and Rapid Fault Isolation Time

A Novel Hybrid DC Circuit Breaker Topology with Current Limi...

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China International Electrical and Energy Conference (CIEEC)

作者： Laicheng Yin Jiayi Liu Yucheng Wu Wei Liu Zhaobo Yiqi Liu College of Mechanical and Electrical Engineerding Northeast Forestry University Harbin China College of Computer and Control Engineering Northeast Forestry University Harbin China

ISBN: (数字)9798350359558

ISBN: (纸本)9798350359565

When fault currents in Modular Multilevel Converter High Voltage Direct Current (MMC-HVDC) transmission systems rise too rapid, the DC circuit breakers (DCCBs) often have insufficient capacity. Therefore, this paper proposes a current-limited hybrid DC circuit breaker (CL-HCB) with fault current limiting and fast fault isolation of the dc grid to reduce the capacity requirement of the DCCB. The topology of the proposed CL-HCB discusses the operation process, metal-oxide arrester (MOA) properties, and parameter design. Besides, the energy dissipation circuit (EDC) is parallel to reduce the energy dissipation in MOA and decrease fault isolation time (FIT), which could reduce the thermal effects of the MOA and improve its reliability. Extensive simulation results verify the working principle and advantages of the proposed CL-HCB. Compared to conventional HCB under the same simulation parameters, the proposed CL-HCB has more advantages in limiting fault current and fault isolation.

关键词： Multilevel converters Limiting Circuit breakers Simulation Energy dissipation High-voltage techniques Topology

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Anomaly-Resistant Decentralized State Estimation Under Minimum Error Entropy With Fiducial Points for Wide-Area Power Systems

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 74-87页

作者： Bogang Qu Zidong Wang Bo Shen Hongli Dong Hongjian Liu the College of Automation Engineering Shanghai University of Electric PowerShanghai 200090China IEEE the Department of Computer Science Brunel University LondonUxbridgeMiddiesex UB83PHUK the College of Information Science and Technology Donghua UniversityShanghai 200051 the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China the Artificial Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast PetroleumDaqing 163318 the Sanya Offshore Oil&Gas Research Institute Northeast Petroleum UniversitySanya 572024China the Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of EducationAnhui Polytechnic UniversityWuhu 2410000 the School of Mathematics and Physics Anhui Polytechnic UniversityWuhu 241000China

This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.

关键词： Decentralized state estimation(SE) measurements with anomalies minimum error entropy unscented Kalman filter wide-area power systems

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ENABLING HIGH SENSITIVITY AIRFLOW MEASUREMENT USING PHASE-CHANGE MATERIALS 26

ENABLING HIGH SENSITIVITY AIRFLOW MEASUREMENT USING PHASE-CH...

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26th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2022

作者： Zhou, Yushan Cao, Yunqi Sepúlveda, Nelson Zhang, Hongjian State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Zhejiang Hangzhou310027 China Department of Electrical and Computer Engineering Michigan State University East LansingMI48824 United States

ISBN: (纸本)9781733419048

A lab-on-a-chip (LOC) thermal mass flow sensor based on microelectromechanical systems (MEMS) technology is designed, fabricated, and characterized. Vanadium dioxide (VO2), a nonlinear phase-change material with 3-order of change in resistance is placed in the down streaming direction of the heat source as the sensing element. The resistance of VO2 is monitored under gas flow rates ranging from 0 to 37.8 μL·s-1 with a maximum sensitivity of 368.56 ppm/(μL·min-1). The studies presented in this research may enable the application of utilizing nonlinear metamaterial in microfluidic LOC sensors with orders of magnitude improvement in sensitivity. © 2022 MicroTAS 2022 - 26th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

关键词： Phase change materials

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Enhanced Robotic Vision System Based on Deep Learning and Image Fusion

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computers, Materials & Continua 2022年第10期73卷 1845-1861页

作者： E.A.Alabdulkreem Ahmed Sedik Abeer D.Algarni Ghada M.El Banby Fathi E.Abd El-Samie Naglaa F.Soliman Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelSheikh UniversityKafrelsheikh33511Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt

Image fusion has become one of the interesting fields that attract researchers to integrate information from different image *** is involved in several *** of the recent applications is the robotic *** application necessitates image enhancement of both infrared(IR)and visible *** paper presents a Robot Human Interaction System(RHIS)based on image fusion and deep *** basic objective of this system is to fuse visual and IR images for efficient feature extraction from the captured ***,an enhancement model is carried out on the fused image to increase its *** image enhancement models such as fuzzy logic,Convolutional Neural Network(CNN)and residual network(ResNet)pre-trained model are utilized on the fusion results and they are compared with each other and with the state-of-the-art *** results prove that the fuzzy logic enhancement gives the best results from the image quality ***,the proposed system can be considered as an efficient solution for the robotic vision problem with multi-modality images.

关键词： Deep learning fuzzy logic image fusion IR images

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Research on coking diagnosis based on semi-supervised Bayesian T-distribution mixed model 4

Research on coking diagnosis based on semi-supervised Bayesi...

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4rth International Conference on Applied Mathematics, Modelling, and Intelligent Computing, CAMMIC 2024

作者： Yang, Hanmei Cui, Delong Li, Qirui Peng, Zhiping Zuo, Jinglong School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin132022 China School of Electronic and Information Engineering Guangdong University of Petrochemical Technology Maoming525000 China School of Computer Science Guangdong University of Petrochemical Technology Maoming525000 China Jiangmen Polytechnic College Jiangmen529090 China

ISBN: (纸本)9781510681637

In the process of ethylene production, the operating data of ethylene cracking furnace not only has the problems of time variability, non-gauss, strong noise, and outlier influence but also the collected data is incomplete, presenting the problem of scarce data with labels and abundant data without labels. To solve the above problems, this paper proposes a soft measurement model based on a semi-supervised Bayesian T-distribution mixture for the coking diagnosis of ethylene cracking furnaces. The model adopts a semi-supervised structure to solve the problem of the small number of data labels, adopts a T-distribution model to ensure the robustness of the model to strong noise and outliers under the Bayesian framework, and solves the solid variation of process data through the mixed model—complexity, non-Gaussian, and nonlinear problems. Finally, the experiment was carried out on the coking data of an ethylene cracking furnace in a petrochemical plant to verify the feasibility and prediction accuracy of the model under the condition of limited label data, and also to verify the robustness of the model to outliers. © 2024 SPIE.

关键词： Statistics

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