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Practical fixed-time adaptive fuzzy control of uncertain nonlinear systems with time-varying asymmetric constraints: a unified barrier function based approach

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Frontiers of Information Technology & Electronic engineering 2024年第9期25卷 1282-1294页

作者： Zixuan HUANG Huanqing WANG Ben NIU Xudong ZHAO Adil M.AHMAD College of Engineering Bohai UniversityJinzhou 121013China College of Mathematical Science Bohai UniversityJinzhou 121013China School of Information Science and Engineering Shandong Normal UniversityJinan 250014China Faculty of Electronic Information and Engineering Dalian University of TechnologyDalian 116024China Communication Systems and Networks Research Group Department of Information TechnologyFaculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia

A practical fixed-time adaptive fuzzy control strategy is investigated for uncertain nonlinear systems with time-varying asymmetric constraints and input quantization. To overcome the difficulties of designing controllers under the state constraints, a unified barrier function approach is employed to construct a coordinate transformation that maps the original constrained system to an equivalent unconstrained one, thus relaxing the time-varying asymmetric constraints upon system states and avoiding the feasibility check condition typically required in the traditional barrier Lyapunov function based control approach. Meanwhile, the “explosion of complexity” problem in the traditional backstepping approach arising from repeatedly derivatives of virtual controllers is solved by using the command filter method. It is verified via the fixed-time Lyapunov stability criterion that the system output can track a desired signal within a small error range in a predetermined time, and that all system states remain in the constraint range. Finally, two simulation examples are offered to demonstrate the effectiveness of the proposed strategy.

关键词： Unified barrier function Time-varying asymmetric state constraints Fuzzy logic systems Fixed-time control Command filter

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Technology Roadmap for Flexible Sensors

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ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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On the Approximation of the Quotient of Two Gaussian Densities for Multiple-Model Smoothing 26

On the Approximation of the Quotient of Two Gaussian Densiti...

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26th International Conference on Information Fusion, FUSION 2023

作者： Liu, Yi Li, Xi Yang, Le Mihaylova, Lyudmila Xue, Yanbo University of Canterbury Department of Electrical and Computer Engineering Christchurch New Zealand National University of Defense Technology State Key Lab of Complex Electromagnetic Environment Effects on Electronics and Information Systems Changsha China University of Sheffield Department of Automatic Control and System Engineering Sheffield United Kingdom Career Science Lab Beijing China

ISBN: (纸本)9798890344854

The quotient of two multivariate Gaussian densities can be written as an unnormalized Gaussian density, which has been applied in some recently developed multiple-model fixed-interval smoothing algorithms. However, this expression is invalid if instead of being positive definite, the covariance of the unnormalized Gaussian density is indefinite (i.e., it has both positive and negative eigenvalues) or undefined (i.e., computing it requires inverting a singular matrix). This paper considers approximating the quotient of two Gaussian densities in this case using two different approaches to mitigate the caused numerical problems. The first approach directly replaces the indefinite covariance of the unnormalized Gaussian density with a positive definite matrix nearest to it. The second approach computes the approximation through solving, using the natural gradient, an optimization problem with a Kullback-Leibler divergence-based cost function. This paper illustrates the application of the theoretical results by incorporating them into an existing smoothing method for jump Markov systems and utilizing the obtained smoothers to track a maneuvering target. © 2023 International Society of Information Fusion.

关键词： Cost functions

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What sentiments are generated in learning experiences with autonomous and multicultural engineering teams? 14

What sentiments are generated in learning experiences with a...

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14th IEEE Global engineering Education Conference, EDUCON 2023

作者： Rodríguez-Galván, Lilia Carolina Ayala-Garcia, Ivo Netali Juárez, Eduardo Daniel Malik, Noreha Abdul Nordin, Anis Nurashikin Rodamporn, Somphop School of Humanities and Education Tecnologico de Monterrey Queretaro Mexico School of Engineering and Science Tecnologico de Monterrey Queretaro Mexico Kulliyah of Engineering International Islamic University Malaysia Department of Electrical and Computer Engineering Kuala Lumpur Malaysia Srinakharinwirot University Faculty of Engineering Bangkok Thailand

ISBN: (纸本)9798350399431

Learning experiences with autonomous and multi-cultural teams are relevant for the future because the composition of the groups and engineering working environments are becoming more ethnically, culturally and linguistically diverse. This paper analyzes of the sentiments generated through learning experiences created for autonomous and multicultural teams. The generated knowledge is helpful for students, academicians and administrators to align expectations and improve management, execution and feedback in learning experiences of this kind. The data was gathered from students' logbooks and written feedback from academicians who participated in two implementations of a summer engineering program at three universities in Malaysia, Mexico and Thailand. The key findings are: 1) the sentiment journey patterns of students and lectures, 2) sentiments from lecturers are manifested in students weeks later, and 3) confidence is the sentiment with the greatest tonality in learning experiences among autonomous and multicultural teams in this learning context. © 2023 IEEE.

关键词： Students

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Melanoma Skin Cancer Identification Using Machine Learning Technique

Melanoma Skin Cancer Identification Using Machine Learning T...

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Sustainable Computing and Smart systems (ICSCSS), International Conference on

作者： R. Lakshmi B. Arthi Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai TN India Department of Computing Technologies Faculty of Engineering and Technology College of Engineering and Technology SRM Institute of Science and Technology Chennai TN India

ISBN: (数字)9798350379990

ISBN: (纸本)9798350391558

Melanoma, a type of skin cancer originating from the cells that produce melanin, has witnessed an alarming rise in its incidence globally, necessitating efficient and accurate detection strategies Being detected early plays a pivotal role in patient prognosis, making the development of precise diagnostic tools imperative. In this research endeavor, we explore the application of optimization algorithms to improve the accuracy and efficiency of melanoma detection using dermoscopy imaging. Leveraging advanced computational techniques, we seek to optimize preprocessing steps, feature extraction, and classification processes. Integration of these optimization methodologies aim to refine the quality of dermoscopy images, extract salient features characteristic of melanoma lesions, and facilitate robust classification using machine learning and deep learning models. This research study intends to contribute to an automated and efficient melanoma detection system, offering early diagnosis and potentially saving lives through timely intervention.

关键词： Accuracy Imaging Melanoma Medical services Green computing Feature extraction Reliability

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Data-driven Causal Association Discovery in Manufacturing Industries 41

Data-driven Causal Association Discovery in Manufacturing In...

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第41届中国控制会议

作者： Yiming Li Jia Xu Li Li Benoit Iung Department of Control Science & Engineering Tongji University Shanghai Research Institute for Intelligent Autonomous Systems Nancy Research Center for Automatic Control (CRAN CNRS UMR 7039)Lorraine University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the development of smart sensors,information storage,processing technology and computer performance,large amounts of operating data collected from production process provide opportunities as well as challenges in remaining useful life(RUL) *** one hand,data-driven analysis approaches are experiencing a fast *** the other hand,the collected variables may be redundant,noisy and high-dimensional for ***,data dimension reduction is applied for eliminating useless *** from correlation-based methods,causal inference methods can obtain reliable models reflecting causal relationships among interesting ***,the latter is more suitable in data dimension *** this study,we use PCMCI+,a causal discovery method based on graph model,that handles both lagged and contemporaneous relationships in multi-variable time *** validate this method on time series data extracted directly from a medium frequency quenching *** obtained results confirm that PCMCI+is able to recognize causal associations among various sensor *** instance,variables in the same process have relatively larger causal relationships than those in different processes.

关键词： causal discovery manufacturing equipment PCMCI+ multi-sensor

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Diabetic Retinopathy Image Classification Using Machine Learning and Local Binary Patterns Features 8

Diabetic Retinopathy Image Classification Using Machine Lear...

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8th International Symposium on Electrical and Electronics engineering, ISEEE 2023

作者： Miron, Mihaela Culea-Florescu, Anisia Moldovanu, Simona Dunarea de Jos University of Galati Faculty of Automation Computers Electrical Engineering and Electronics Department of Computer Science and Information Technology Galati Romania Dunarea de Jos University of Galati Faculty of Automation Computers Electrical Engineering and Electronics Department of Electronics and Telecommunications Galati Romania

ISBN: (纸本)9798350301670

Diabetic Retinopathy (DR) is a condition caused by diabetes that affects the blood vessels in the retina. Detecting the disease early and providing appropriate treatment are crucial in slowing its progression. Therefore, there is great potential in utilizing Machine Learning (ML) to improve the identification and monitoring of DR development in patients. Our study aims to explore the performance of six ML algorithms, namely Random Forest (RF), Adaptive Boosting (AB), K-Nearest Neighbor (K-NN), Gaussian Naive Bayes (GNB), Support Vector Machine (SVM), and Quadratic Discriminant Analysis (QDA), in two binary classifications involving three classes: non-diabetic retinopathy (NoDR), moderate retinopathy (MR), and severe retinopathy (SV). These ML algorithms were applied to ten features extracted using local binary patterns (LBP). The first classification task involved distinguishing between NoDR and MR, while the second task involved differentiating between NoDR and SV. The RF technique achieved the highest classification accuracy, with 0.912 for the first task and 0.94 for the second task. © 2023 IEEE.

关键词： Local binary pattern

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A Drones Optimal Path Planning Based on Swarm Intelligence Algorithms

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computers, Materials & Continua 2022年第7期72卷 365-380页

作者： Mahmoud Ragab Ali Altalbe Abdullah Saad Al-Malaise ALGhamdi SAbdel-khalek Rashid A.Saeed Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia Center of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah 21589Saudi Arabia Information Systems Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Mathematics Faculty of ScienceAl-Azhar UniversityNaser City 11884CairoEgypt Department of Mathematics Faculty of ScienceTaif UniversityTaifSaudi Arabia Department of Mathematics Faculty of ScienceSohag UniversitySohagEgypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia

The smart city comprises various interlinked elements which communicate data and offers urban life to *** Aerial Vehicles(UAV)or drones were commonly employed in different application areas like agriculture,logistics,and *** improving the drone flying safety and quality of services,a significant solution is for designing the Internet of Drones(IoD)where the drones are utilized to gather data and people communicate to the drones of a specific flying region using the mobile devices is for constructing the Internet-of-Drones,where the drones were utilized for collecting the data,and communicate with *** addition,the SIRSS-CIoD technique derives a tuna swarm algorithm-based clustering(TSA-C)technique to choose cluster heads(CHs)and organize clusters in IoV ***,the SIRSS-CIoD technique involves the design of a biogeography-based optimization(BBO)technique to an optimum route selection(RS)*** design of clustering and routing techniques for IoD networks in smart cities shows the novelty of the study.A wide range of experimental analyses is carried out and the comparative study highlighted the improved performance of the SIRSS-CIoD technique over the other approaches.

关键词： Drones smart city swarm intelligence route selection internet of drones networking

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Fiction Gene : A Thai Genre Based Fiction Visualization Testimonial System 28

Fiction Gene : A Thai Genre Based Fiction Visualization Test...

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28th International computer science and engineering Conference, ICSEC 2024

作者： Wattanapornprom, Warin Innarong, Chatchaya Kerdpra, Isara Treesutrummas, Chisanupong Lertampaiporn, Supatcha Susutti, Wittawin King Mongkut's University of Technology Thonburi Faculty of Science Department of Mathematics Bangkok Thailand NSTDA King Mongkut's University of Technology Thonburi Biochemical Engineering and Systems Biology Research Group Bangkok Thailand

ISBN: (纸本)9798350366860

In today's digital era, fiction has become immensely popular and accessible through various channels, particularly online platforms where some content requires payment for access. Readers, therefore, seek fictions that align with their specific genre preferences to make informed reading choices. To assist in this process, we have developed a sophisticated genre-based fiction visualization testimonial system. This system leverages TF-IDF natural language processing algorithms for extracting key features and employs machine learning, specifically Naive Bayes algorithms, for accurate text classification. Implemented as a user-friendly sample website, the system visually represents fiction genres through pie charts and line charts. Our model achieved up to 91% accuracy in predicting the primary genre of fiction, thereby providing valuable support for readers in selecting fictions that best meet their preferences. © 2024 IEEE.

关键词： Visualization

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Dynamic Hierarchical Reinforcement Learning Framework for Energy-Efficient 5G Base Stations in Urban Environments

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IEEE Transactions on Mobile Computing 2025年

作者： Xu, Dianlei Su, Xiang Premsankar, Gopika Wang, Huandong Tarkoma, Sasu Hui, Pan University of Helsinki Department of Computer Science Helsinki00014 Finland Department of Electronic Engineering Beijing100084 China University of Helsinki Department of Agricultural Sciences Helsinki00014 Finland Aalto University Department of Information and Communications Engineering Finland University of Oulu Faculty of Information Technology and Electrical Engineering Oulu90014 Finland The Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong

The energy consumption of 5G base stations (BSs) is significantly higher than that of 4G BSs, creating challenges for operators due to increased costs and carbon emissions. Existing solutions address this issue by switching off BSs during specific periods or forming cooperation coalitions where some BSs deactivate while others serve users. However, these approaches often rely on fixed geographic configurations, making them unsuitable for urban areas with numerous BSs and mobile users. To tackle these challenges, we propose a hierarchical reinforcement learning (RL) framework for energy conservation in large-scale 5G networks. In the upper-layer, we propose a deep Q-network integrated with a graph convolutional network that dynamically groups BSs into coalitions from a macro perspective. This layer focuses on high-level coalition formation to optimize system-wide energy efficiency by considering the global state of the network. In the lower-layer, we combine attention mechanism with multi-agent RL and graph convolutional networks to design a scalable algorithm that maximizes local energy efficiency through optimizing the cooperation within each coalition. These two layers align global coalition dynamics with local intra-coalition cooperation to achieve system-wide energy optimization. Moreover, we accurately model large-scale urban 5G scenarios leveraging a high-fidelity network simulator, which enables our RL framework to learn from real-world feedback. Extensive experiments conducted with the simulator demonstrate that our proposed framework achieves remarkable energy savings of up to 75.6%, significantly outperforming baseline approaches. These findings highlight the effectiveness and superiority of our hierarchical RL optimization framework in addressing the energy consumption challenges faced by large-scale 5G networks. © 2002-2012 IEEE.

关键词： 5G mobile communication systems

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