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2023 China Automation Congress, CAC 2023

作者： Du, Sheng Ma, Xian Li, Xiang Wu, Min Cao, Weihua Pedrycz, Witold School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Faculty of Engineering and Natural Sciences Department of Computer Engineering Istanbul Sariyer Turkey

ISBN: (纸本)9798350303759

Anomaly detection is essential to ensure the safety of industrial processes. This paper presents an anomaly detection approach based on the probability density estimation and principle of justifiable granularity. First, time series data are transformed into a two-dimensional information granule by the principle of justifiable granularity. Then, the test statistic is constructed, and the probability density and cumulative distribution functions of the test statistic are calculated. Next, the confidence level determines the test threshold. Finally, the time series data of a key parameter in the sintering process is used as a case study. The experimental result demonstrates that the proposed approach can detect abnormal time series data effectively, providing an accurate and effective solution for detecting time series anomalies in industrial processes. © 2023 IEEE.

关键词： Time series

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Natural Human Skin‑Inspired Wearable and Breathable Nanofiber‑based Sensors with Excellent Thermal Management Functionality

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Advanced Fiber Materials 2024年第6期6卷 1955-1968页

作者： Peng Wang Xiaodan Li Guifen Sun Guoqing Wang Qing Han Chuizhou Meng Zhonghe Wei Yang Li School of Mechanical Engineering University of JinanJinan 250022China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China State Key Laboratory for Reliability and Intelligence of Electrical Equipment Engineering Research Center of Ministry of Education for Intelligent Rehabilitation Device and Detection TechnologyHebei Key Laboratory of Smart Sensing and Human‑Robot InteractionSchool of Mechanical EngineeringHebei University of TechnologyTianjin 300401China Shandong Provincial Key Laboratory of Network‑Based Intelligent Computing School of Information Science and EngineeringUniversity of JinanJinan 250022China Network Information Center Department of Computer ScienceQilu University of Technology(Shandong Academy of Sciences)Jinan 250353China School of Integrated Circuits Shandong UniversityJinan 250101China

Wearable sensors have been rapidly developed for application in various human monitoring ***,the wearing comfort and thermal properties of these devices have been largely ignored,and these characteristics urgently need to be ***,we develop a wearable and breathable nanofiber-based sensor with excellent thermal management functionality based on passive heat preservation and active Joule heating *** multifunctional device consists of a micropatterned carbon nanotube(CNT)/thermoplastic polyurethane(TPU)nanofiber electrode,a microporous ionic aerogel electrolyte and a microstructured Ag/TPU nanofiber *** to the presence of a supercapacitive sensing mechanism and the appli-cation of microstructuration,the sensor shows excellent sensing performance,with a sensitivity of 24.62 ***,due to the overall porous structure and hydrophobicity of TPU,the sensor shows good breathability(62 mm/s)and water repellency,with a water contact angle of 151.2°.In addition,effective passive heat preservation is achieved by combining CNTs with high solar absorption rates(85%)as the top layer facing the outside,aerogel with a low thermal conductivity(0.063 W m-1 k-1)as the middle layer for thermal insulation,and Ag with a high infrared reflectance rate as the bottom layer facing the *** warming,this material yields a higher temperature than ***,the active Joule heat-ing effect is realized by applying current through the bottom resistive electrode,which can quickly increase the temperature to supply controlled warming on *** proposed wearable and breathable sensor with tunable thermal properties is promising for monitoring and heat therapy applications in cold environments.

关键词： Wearable sensor Breathable Personal thermal management Electrospun nanofibers Joule heating

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A Multi-Player Potential Game Approach for Sensor Network Localization with Noisy Measurements 63

A Multi-Player Potential Game Approach for Sensor Network Lo...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Xu, Gehui Chen, Guanpu Fidan, Baris Hong, Yiguang Qi, Hongsheng Parisini, Thomas Johansson, Karl H. Kth Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm100 44 Sweden University of Waterloo Department of Mechanical and Mechatronics Engineering WaterlooONN2L 3G1 Canada Tongji University Department of Control Science and Engineering shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China University of Chinese Academy of Sciences School of Mathematical Sciences Beijing China Aalborg University Department of Electronic Systems Denmark Imperial College London Department of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom University of Trieste Department of Engineering and Architecture Italy

ISBN: (纸本)9798350316339

Sensor network localization (SNL) is a challenging problem due to its inherent non-convexity and the effects of noise in inter-node ranging measurements and anchor node position. We formulate a non-convex SNL problem as a multiplayer non-convex potential game and investigate the existence and uniqueness of a Nash equilibrium (NE) in both the ideal setting without measurement noise and the practical setting with measurement noise. We first show that the NE exists and is unique in the noiseless case, and corresponds to the precise network localization. Then, we study the SNL for the case with errors affecting the anchor node position and the inter-node distance measurements. Specifically, we establish that in case these errors are sufficiently small, the NE exists and is unique. It is shown that the NE is an approximate solution to the SNL problem, and that the position errors can be quantified accordingly. Based on these findings, we apply the results to case studies involving only inter-node distance measurement errors and only anchor position information inaccuracies. © 2024 IEEE.

关键词： Nash equilibrium

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Classification of skin lesions using morpho-granulometry features derived from color clusters

Classification of skin lesions using morpho-granulometry fea...

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International Conference on System Theory, control, and Computing (ICSTCC)

作者： Gigi Tăbăcaru Simona Moldovanu Marian Barbu Department of Automatic Control and Electrical Engineering Faculty of Automation Computers Electrical Engineering and Electronics "Dunarea de Jos" University of Galati Galati Romania Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics The Modelling & Simulation Laboratory "Dunarea de Jos" University of Galati Galati Romania

ISBN: (数字)9798350364293

ISBN: (纸本)9798350364309

The skin lesion can be thought of as a biological system, so the morpho-granulometry of significant color clusters found in skin lesions is one of the elements that reproduce in a natural way the structure of the lesion, this novelty is highlighted in this study. Important features of skin lesions can be modulated by fusing neural networks (NN) and machine learning (ML). By choosing the nevus and melanoma classes, the primary goal was accomplished, and three databases were used to test the methodology. The characteristics based on morpho-granulometry allowed for the identification of microstructure within the images, which can be very helpful in characterizing the biological system. Based on random forest (RF) and extreme gradient boosting (XGboost) classifiers, this work aimed to improve the classification performance of important feature selection. The selected features from three free image databases with three NNs were classified. In a binary classification of nevus vs. melanoma, the results showed that the pattern recognition neural network (PRNN), according to the PH2 database, provided an accuracy of 0.923 and an F1-score of 0.876. The classification is interpretable if it is not validated. In our study, the best results were verified with a logistic regression (LR) classifier.

关键词： Accuracy Recurrent neural networks Image color analysis Melanoma Biological systems Artificial neural networks Feature extraction Skin Lesions Classification tree analysis

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On the conceptualization of total disturbance and its profound implications

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Science China(Information sciences) 2020年第2期63卷 221-223页

作者： Sen CHEN Wenyan BAI Yu HU Yi HUANG Zhiqiang GAO Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences Beijing Aerospace Automatic Control Institute Center for Advanced Control Technologies Department of Electrical Engineering and Computer ScienceCleveland State University

Dear editor,How to deal with uncertainties and/or disturbances is a central issue pushing the development of both control science and control technology. Among various approaches, the active disturbance rejection control (ADRC) has been successfully implemented in various industrial practices because of its uniqueness in concepts, simplicity

关键词： ESO On the conceptualization of total disturbance and its profound implications

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Efficiency Optimization of Induction Motor Using a Modified Gray Wolf Optimization

Efficiency Optimization of Induction Motor Using a Modified ...

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International Conference on sciences and Techniques of automatic control and computer engineering (STA)

作者： Oussama Zeghba Salim Chakroun Ali Aillane Research Laboratory on the Electrical Engineering University of M'Sila Algeria Laboratory of Sciences and Techniques of Automatic Control and Computer Engineering (Lab-STA) National School of Engineering of Sfax (ENIS) University of Sfax Sfax Tunisia

ISBN: (纸本)9781665482622

In this research, a method for improving the efficiency of induction motors based on the modified gray wolf optimizer (mGWO) is proposed and examined. In order to reduce the overall copper and iron losses of the machine, the efficiency improvement technique entails modifying the geometric dimensions with regard to the lower and upper bound of those parameters. A comparison between the findings achieved utilizing the mGWO and GAs approach is done, and some simulation performances are shown along with a comparison of efficiency, electric current, and torque. The approach mGWO provided good results and required less time to extract results once the simulation results were obtained using the aforementioned methods.

关键词： Energy consumption Induction motors Upper bound Torque Simulation Iron Data models

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Efficient Frameworks for EEG Epileptic Seizure Detection and Prediction

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Annals of Data Science 2022年第2期9卷 393-428页

作者： Emara, Heba M. Elwekeil, Mohamed Taha, Taha E. El-Fishawy, Adel S. El-Rabaie, El-Sayed M. El-Shafai, Walid El Banby, Ghada M. Alotaiby, Turky Alshebeili, Saleh A. Abd El-Samie, Fathi E. Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Security Engineering Laboratory Department of Computer Science Prince Sultan University Riyadh11586 Saudi Arabia Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt KACST Riyadh Saudi Arabia King Saud University Riyadh Saudi Arabia Department of Electrical Engineering King Saud University Riyadh11421 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh21974 Saudi Arabia

Seizure detection and prediction are a very hot topics in medical signal processing due to their importance in automatic medical diagnosis. This paper presents three efficient frameworks for applications related to electroencephalogram (EEG) signal processing. The first one is an automatic seizure detection framework based on the utilization of scale-invariant feature transform (SIFT) as an extraction tool. The second one depends on the utilization of the fast Fourier transform (FFT) and an artificial neural network for epileptic seizure prediction. Finally, an automated patient-specific framework for channel selection and seizure prediction is presented based on FFT. The simulation results show the success of the proposed frameworks for automated medical diagnosis. © 2021, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Fast Fourier transforms

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A Learning-based Adaptive Compliance Method for Symmetric Bi-manual Manipulation

arXiv

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arXiv 2023年

作者： Cao, Yuxue Zhao, Wenbo Wang, Shengjie Zheng, Xiang Ma, Wenke Wang, Zhaolei Zhang, Tao Beijing Institute of Control Engineering China Department of Automation Tsinghua University China Institute for Interdisciplinary Information Sciences Tsinghua University China Department of Computer Science City University of Hong Kong Hong Kong Qian Xuesen Laboratory of Space Technology China Beijing Aerospace Automatic Control Institute China

Symmetric bi-manual manipulation is an essential skill in on-orbit operationsdue to its potent load capacity. Previous works have applied compliant controlto maintain the stability of manipulations. However, traditional methods haveviewed motion planning and compliant control as two separate modules, which canlead to conflicts with the simultaneous change of the desired trajectory andimpedance parameters in the presence of external forces and ***, the joint usage of these two modules requires experts to manuallyadjust parameters. To achieve high efficiency while enhancing adaptability, wepropose a novel Learning-based Adaptive Compliance algorithm (LAC) thatimproves the efficiency and robustness of symmetric bi-manual ***, the algorithm framework integrates desired trajectory generationand impedance-parameter adjustment under a unified framework to mitigatecontradictions and improve efficiency. Second, we introduce a centralizedActor-Critic framework with LSTM networks preprocessing the force states,enhancing the synchronization of bi-manual manipulation. When evaluated indual-arm peg-in-hole assembly experiments, our method outperforms baselinealgorithms in terms of optimality and robustness. Copyright © 2023, The Authors. All rights reserved.

关键词： Motion planning

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The strong substructure and feature attention mechanism for image semantic segmentation

The strong substructure and feature attention mechanism for ...

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作者： Zhang, Yuhang Ren, Hongshuai Yang, Wensi Wang, Yang Ye, Kejiang Xu, Cheng-Zhong Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China Alibaba Cloud Alibaba Group Hangzhou China State Key Laboratory of IoT for Smart City University of Macau China

Semantic segmentation is a hot topic in computer vision and various deep learning networks are designed to achieve higher accuracy on that by fully exploring the capability of neural networks. This paper aims to address the issue and proposes the substructures with novelty for popular networks. Meanwhile, we present a cross-channel structure, which simultaneously reduces parameter while the kernel size becomes larger. After that, to overcome the weakness of insufficient dataset which refers to satellite image data, we propose a feature attention mechanism with generative adversarial network to enhance the images' features. We show the recognition result on the satellite image dataset with a large picture. This paper evaluates substructures on the PASCAL VOC2012 dataset and improves the mIOU from 74.68% to 88.15%. © 2020 John Wiley & Sons, Ltd.

关键词： Image recognition

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Online Linear Quadratic Tracking with Regret Guarantees

arXiv

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arXiv 2023年

作者： Karapetyan, Aren Bolliger, Diego Tsiamis, Anastasios Balta, Efe C. Lygeros, John The Automatic Control Laboratory Department of Information Technology and Electrical Engineering ETH Zürich Zürich8092 Switzerland School of Engineering ZHAW Zurich University of Applied Sciences Winterthur8400 Switzerland Control and Automation Group Inspire AG Zürich8005 Switzerland

Online learning algorithms for dynamical systems provide finite time guarantees for control in the presence of sequentially revealed cost functions. We pose the classical linear quadratic tracking problem in the framework of online optimization where the time-varying reference state is unknown a priori and is revealed after the applied control input. We show the equivalence of this problem to the control of linear systems subject to adversarial disturbances and propose a novel online gradient descent-based algorithm to achieve efficient tracking in finite time. We provide a dynamic regret upper bound scaling linearly with the path length of the reference trajectory and a numerical example to corroborate the theoretical guarantees. © 2023, CC BY.

关键词： Cost functions

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