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第43届中国控制会议

作者： Hongchenyu Yang Tai-Cheng Yang Chen Peng Engang Tian Yang Song Department of Engineering and Design University of Sussex School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In control theory using the state-space method,it is often assumed that a matrix is of full rank to further mathematical development. Few people stop to ask two questions:(1) How far is the 'distance' between the given full-rank matrix and a non-full-rank matrix?,and(2) How does this 'distance' affect control? In robust system analysis and design,in addition to verifying that a system is stable,one also measures how far it is from an unstable system. The simplest stability measurement for a single-input-single-output(SISO) linear system is the gain margin and phase margin. Similarly,beyond a 'Yes' or 'No' answer,for a full-rank matrix in control,we should ask the above two questions. Pursuing such questions leads to a lot of interesting and useful results. Some of them are well-documented in the literature;some are yet to be fully explored. This paper illustrates some existing research and proposes some future studies. In general,we can review all control lemmas and theorems based on matrix full-rank conditions to explore further studies. The study can also extend to non-linear systems. The basic nonlinear system controllability(observability) tests are based on if the relevant matrices,constructed using Lie Bracket(Lie Derivative),are of full rank. Furthermore,similar studies can be on another important matrix property:positiveness,and on more challenging research into the degrees of controllability and observability for networked control systems.

关键词： Review Basic Concepts Explore the Possibilities of Further Studies

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Optimizing Web Server Performance: A Comparative Analysis of Central Manager and Round Robin Load Balancing Algorithms 4

Optimizing Web Server Performance: A Comparative Analysis of...

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4th International Conference on electrical engineering and computer science, ICECOS 2024

作者： Permana Arrasyid, Fahmi Stiawan, Deris Afifah, Nurul Heryanto, Ahmad Azhar, Iman Saladin B. Bardadi, Ali Yudho Suprapto, Bhakti Pahendra Anto Saputra, Iwan Sriwijaya University COMNETS Rerearch Group Faculty of Camp. Science Palembang Indonesia Sriwijaya University Faculty of Comp. Science Computer Engineering Dept. Palembang Indonesia Sriwijaya University Faculty of Comp. Science Information System Dept. Palembang Indonesia Sriwijaya University Faculty of Engineering Electrical Engineering Dept. Palembang Indonesia

ISBN: (纸本)9798350368253

Central manager algorithm has a lower average throughput compared to the round robin algorithm. This is evidenced by a significant decrease in throughput values during measurements. Central manager algorithm provides a faster average response time than round robin algorithm, despite experiencing an increase in response time values over time. Central manager algorithm shows a higher request loss rate and many requests are not served. Under normal performance conditions, both algorithms yield the same average request loss rate, achieving stable values without failed requests. The central manager algorithm ensures relatively balanced resource availability, including CPU and memory usage, across each slave web server compared to the round robin algorithm. The results show that increasing the number of clients and client requests during system testing to better observe server resource availability and load distribution performance. For future research, it is recommended to increase the number of clients in the system testing to enhance server load and to introduce client request actions on the web server to further highlight resource availability on each web server. © 2024 IEEE.

关键词： Response time (computer systems)

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ANIMC: A Soft Approach for Autoweighted Noisy and Incomplete Multiview Clustering

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2022年第2期3卷 192-206页

作者： Fang, Xiang Hu, Yuchong Zhou, Pan Wu, Dapeng Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering The School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Information Storage System Ministry of Education of China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Department of Electrical and Computer Engineering University of Florida GainesvilleFL32611 United States

Multiview clustering has wide real-world applications because it can process data from multiple sources. However, these data often contain missing instances and noises, which are ignored by most multiview clustering methods. Missing instances may make these methods difficult to use directly, and noises will lead to unreliable clustering results. In this article, we propose a novel autoweighted noisy and incomplete multiview clustering (ANIMC) approach via a soft autoweighted strategy and a doubly soft regular regression model. First, by designing adaptive semiregularized nonnegative matrix factorization, the soft autoweighted strategy assigns a proper weight to each view and adds a soft boundary to balance the influence of noises and incompleteness. Second, by proposing θ-norm, the doubly soft regularized regression model adjusts the sparsity of our model by choosing different θ. Compared with previous methods, ANIMC has three unique advantages: 1) it is a soft algorithm to adjust our approach in different scenarios, thereby improving its generalization ability;2) it automatically learns a proper weight for each view, thereby reducing the influence of noises;3) it performs doubly soft regularized regression that aligns the same instances in different views, thereby decreasing the impact of missing instances. Extensive experimental results show its superior advantages over other state-of-the-art works. © 2020 IEEE.

关键词： Clustering algorithms

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Subject-independent emotion recognition of EEG signals using graph attention-based spatial-temporal pattern learning 41

Subject-independent emotion recognition of EEG signals using...

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第41届中国控制会议

作者： Yiwen Zhu Yeshuang Guo Wenzhe Zhu Lare Di Zhong Yin School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Engineering Research Center of Optical Instrument and System Ministry of EducationShanghai Key Lab of Modern Optical SystemUniversity of Shanghai for Science and Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Electroencephalography(EEG) reveals human brain activities and becomes an essential solution for exploring human intrinsic emotional *** this study,we proposed a graph attention-based spatial-temporal pattern learning method called TAGAT to take full advantage of spatial structure of EEG channels and take the nonstationary of emotions into *** attention mechanism is applied to compute weight coefficients of different spatial and temporal *** alleviate differences between subjects,a domain discriminator is added to the model based on domain adaptation to tackle subject-independent EEG emotion recognition *** on the DEAP database,our method achieves the accuracy of 56.56% and 58.91% of arousal and valence dimensions for subject-independent emotion *** effectiveness of T-AGAT method has been demonstrated when compared to other existing common methods.

关键词： Emotion recognition electroencephalography deep learning transfer learning pattern learning

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The Bayesian Network Method for Handling Cyclic Loops Based on Information Flow 6

The Bayesian Network Method for Handling Cyclic Loops Based ...

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6th IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2024

作者： Zhou, Dongliang Liu, Jie Yang, Xiaohua Wei, Ying Wu, Zhiqiang Li, Meng University of South China School of Computer Science Hunan Hengyang China University of South China School of Electrical Engineering Hunan Hengyang China China Nuclear Power Institute Research and Design Institute Sichuan Chengdu China

ISBN: (纸本)9798350389418

Accurately identifying fault sources in industrial systems is essential for ensuring system safety and optimizing performance. Due to cyclic loops, traditional Bayesian networks often encounter difficulties when dealing with complex systems, which can lead to misjudgments, especially in scenarios involving causal feedback. This paper proposes an improved method based on information flow, utilizing the Liang-Kleeman information flow theory to handle C-R structure cyclic loops within Bayesian networks. By quantifying the strength of causal relationships in cyclic loops, the method effectively identifies and eliminates the weakest causal link, transforming it into a temporal relationship and simplifying the structure into an acyclic form. Experiments were conducted on a C-R structure feedback system to validate the new method's performance under high-noise conditions. The results demonstrate that the process improves the accuracy of causal relationship identification and exhibits superior robustness in noisy environments, significantly enhancing fault diagnosis accuracy and real-time capabilities. This study provides novel solutions and tools for fault diagnosis in complex industrial systems. © 2024 IEEE.

关键词： Bayesian networks

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Reference Tracking for Constrained Uncertain Linear systems by Stochastic MPC

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IFAC-PapersOnLine 2023年第2期56卷 10421-10427页

作者： Jannik Hahn Olaf Stursberg Control and System Theory Dept. of Electrical Engineering and Computer Science University of Kassel 34121 Kassel Germany

This paper addresses model predictive control of a class of linear systems subject to additive stochastic disturbances and constraints. The underlying stochastic optimal control problem combines inverse cumulative distribution functions with ellipsoid-in-polyhedron formulations to reduce the conservatism induced by constraint satisfaction. By use of terminal constraints and time-varying weights within the cost functional, the presented control scheme satisfies criteria for mean-square stability and can be adapted to reference-tracking problems for arbitrary reference signals.

关键词： Probabilistic Constraints Mean-Square Stability Predictive Control Stochastic Control Uncertain systems

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Critical Factors of Immersive Learning in Higher Education: A systematic Literature Review 10

Critical Factors of Immersive Learning in Higher Education: ...

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10th International Conference on ICT for Smart Society, ICISS 2023

作者： Sunardi Meyliana Ramadhan, Arief Rosmansyah, Yusep Bina Nusantara University BINUS Graduate Program Doctor of Computer Science Computer Science Department Jakarta Indonesia School of Information System Bina Nusantara University Information System Departement Jakarta Indonesia School of Computing Telkom University Bandung Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia

ISBN: (纸本)9798350339543

Immersive learning has gained significant attention with the rising trend of spatial computing, particularly in the after-pandemic era. Numerous research has explored the potential of immersive learning in higher education, primarily on the educational sector. However, prior research has frequently focused too narrowly on the effects of technology and neglected to address the crucial element influencing successful immersive learning in higher education. This study seeks to pinpoint the crucial element contributing to the development of immersive learning experiences. The methodology uses a systematic literature review (SLR) from 2018 up to 2023 to investigate the critical factors of immersive Learning in Higher Education. From the 728 papers initially retrieved, 274 were considered potential candidates, and ultimately, 86 articles were selected based on their relevance to the research question. The results reveal that the critical factors include learning design, technology, immersion, engagement, interactivity, and usability. Academic interests will benefit from this SLR's consequences as institutions create models for designing suitable immersive learning, especially within the context of higher education. © 2023 IEEE.

关键词： E-learning

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Optimal Load Forecasting Model for Peer-to-Peer Energy Trading in Smart Grids

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computers, Materials & Continua 2022年第1期70卷 1053-1067页

作者： Lijo Jacob Varghese K.Dhayalini Suma Sira Jacob Ihsan Ali Abdelzahir Abdelmaboud Taiseer Abdalla Elfadil Eisa Department of Electrical and Electronics Engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Electrical and Electronics Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Computer Science and Engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversity of Malaya50603Kuala LumpurMalaysia Department of Information Systems King Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Information Systems-Girls Section King Khalid UniversityMahayil62529Saudi Arabia

Peer-to-Peer(P2P)electricity trading is a significant research area that offers maximum fulfilment for both prosumer and *** also decreases the quantity of line loss incurred in Smart Grid(SG).But,uncertainities in demand and supply of the electricity might lead to instability in P2P market for both prosumer and *** recent times,numerous Machine Learning(ML)-enabled load predictive techniques have been developed,while most of the existing studies did not consider its implicit features,optimal parameter selection,and prediction *** order to overcome fulfill this research gap,the current research paper presents a new Multi-Objective Grasshopper Optimisation Algorithm(MOGOA)with Deep Extreme Learning Machine(DELM)-based short-term load predictive technique i.e.,MOGOA-DELM model for P2P Energy Trading(ET)in *** proposed MOGOA-DELM model involves four distinct stages of operations namely,data cleaning,Feature Selection(FS),prediction,and parameter *** addition,MOGOA-based FS technique is utilized in the selection of optimum subset of ***,DELM-based predictive model is also applied in forecasting the load *** proposed MOGOA model is also applied in FS and the selection of optimalDELM parameters to improve the predictive *** inspect the effectual outcome of the proposed MOGOA-DELM model,a series of simulations was performed using UK Smart Meter *** the experimentation procedure,the proposed model achieved the highest accuracy of 85.80%and the results established the superiority of the proposed model in predicting the testing data.

关键词： Peer to Peer energy trade smart grid load forecasting machine learning feature selection

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system Modelling, Numerical Simulations and Experimental Validation of High Capacity FSO Data Transmission in DWDM Communication Employing Optical Frequency Comb 24

System Modelling, Numerical Simulations and Experimental Val...

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24th IEEE International Conference on Numerical Simulation of Optoelectronic Devices, NUSOD 2024

作者： Rajaram, Narmada Avazpour, Mahrokh Barry, Liam Hinzer, Karin Hall, Trevor Atieh, Ahmad School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada School of Electronic Engineering Dublin City University Radio and Optics Communications Laboratory GlasnevinDublin 9 Ireland University of Ottawa Optiwave System Inc 7 Capella Court Ottawa Canada

ISBN: (纸本)9798350390537

Dense Wavelength Division Multiplexing (DWDM) optical technology allows transmission of many wavelengths in a single optical channel. In this paper, system modelling and numerical simulations are demonstrated for high-capacity data transmission using an Optical Frequency Comb (OFC). An OFC is generated using fiber loop modulation technique and simulations are carried out using commercially available simulation software -Optisystem. An OFC with excellent flatness is obtained, which is essential for noise and error reduction. Each comb line is modulated with data and the DWDM multiplexed signal is transmitted over a free-space optical (FSO) channel. The system performance is assessed in terms of Bit Error Rate (BER) and range of the FSO channel. Our experimental results demonstrate that our system aligns well with simulation and can generate an OFC confirming the potential of our approach for applications such as optical communication networks. © 2024 IEEE.

关键词： Bit error rate

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A robust multi-objective optimization algorithm for accurate parameter estimation for solar cell models

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Soft Computing 2024年第19期28卷 11265-11277页

作者： Singla, Manish Kumar Gupta, Jyoti Alsharif, Mohammed H. Kim, Mun-Kyeom Aljaidi, Mohammad Safaraliev, Murodbek Department of Interdisciplinary Courses in Engineering Chitkara University Institute of Engineering & ampTechnology Chitkara University Punjab India Applied Science Research Center Applied Science Private University Amman11931 Jordan School of Engineering and Technology K. R. Mangalam University Gurgaon Haryana122003 India Department of Electrical Engineering College of Electronics and Information Engineering Sejong University 209 Neungdong-Ro Gwangjin-Gu Seoul05006 Korea Republic of School of Energy System Engineering Chung-Ang University 84 Heukseok-Ro Dongjak-Gu Seoul06974 Korea Republic of Department of Computer Science Zarqa University Zarqa13110 Jordan Department of Automated Electrical Systems Ural Federal University Yekaterinburg620002 Russia

The accuracy of solar cell models is crucial for enhancing the performance of solar photovoltaic (PV) systems. However, existing solar cell models lack precise parameters, and the manufacturer's datasheet does not provide the required information for reliable modeling. Consequently, accurate parameter estimation becomes necessary. This paper presents a simple multi-objective optimization algorithm (Hybrid Particle Swarm Optimization and Rat Search Algorithm (PSORSA)) designed to estimate cell parameters based on this observation. Unlike other optimization algorithms addressing this issue, the proposed algorithm aims to overcome challenges related to local minima and premature convergence, which often lead to suboptimal results. The paper focuses on assessing the reliability of the proposed algorithm by comparing its performance with other well-known optimization algorithms. The proposed optimizing algorithm is tested on the CEC 2019 benchmark function. Experimental results (RMSE), including statistical analysis, validate the algorithm's effectiveness by comparing them with other algorithms. At the end, non-parametric test is performed to justify the outcomes, vouching for the better performance of the proposed algorithm. The findings demonstrate that the proposed algorithms are particularly well-suited for estimating solar PV models. With its simple structure and high accuracy, the proposed algorithm exhibits great potential for various applications in the field of solar energy. Moreover, its computational efficiency and ease of implementation further contribute to its practicality. © The Author(s) 2024.

关键词： Solar cells

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