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62nd IEEE Conference on Decision and control, CDC 2023

作者： Wang, Dan Chen, Wei Johansson, Karl H. Kth Royal Institute of Technology Division of Decision and Control Systems Stockholm Sweden Peking University State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science Beijing China

ISBN: (纸本)9798350301243

A new notion of phase of multi-input multi-output (MIMO) systems was recently defined and studied, leading to new understandings in various fronts including a formulation of small phase theorem, a performance criterion named H∞ phase sector, and a sectored real lemma, etc. In this paper, we define a new notion of H2T-dissipativity and show the connection between the phase of a multivariable linear time-invariant (LTI) system and the H2T-dissipativity. The H2T-dissipativity, roughly speaking, is dissipativity restricted to the time-domain H2 space which consists of L2 signals with only positive frequency components. In addition, by exploiting the newly defined H2T- dissipativity, we also study the phase of a feedback system and provide a physical interpretation of the sectored real lemma. © 2023 IEEE.

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Pareto Improvement for Noncooperative systems With Vector-valued Payoff Functions

Pareto Improvement for Noncooperative Systems With Vector-va...

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IEEE Conference on Decision and control

作者： Zehui Guo Tomohisa Hayakawa Department of Systems and Control Engineering Tokyo Institute of Technology Meguro Tokyo Japan

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Definition of weak Pareto improvement is given for noncooperative systems with vector-valued payoff functions. The region where a system trajectory is Pareto improving is characerized. Some necessary and sufficient conditions are given for when the system trajectory is (weak) Pareto improving in the entire state space. We provide several numerical examples to illustrate our results.

关键词： Sufficient conditions Sensitivity Aerospace electronics Vectors Trajectory

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A Deep Learning Based Personal Authentication Method Using sEMG Signal 41

A Deep Learning Based Personal Authentication Method Using s...

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第41届中国控制会议

作者： Lina Tong Mingjia Zhang Daisong Liu Hanghang Ma Yuxiang Zhang Liang Peng School of Mechanical Electronic & Information Engineering Chinese University of Mining and Technology-Beijing State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChina Academy of Science

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Personal authentication means that the relevant system confirms whether the identity of the user is real,legal and unique.A safe and convenient personal authentication method is a core for guarantee the security of our information and *** Electromyography(sEMG),which exists on the surface of the skin,is a good signal to achieve personal authentication,for it is difficult to be extracted and *** this paper,a new personal authentication method using forearm sEMG is ***,8-channel sEMG signals are recorded by Myo armband that is placed on right forearm of 14 subjects who perform the same hand open ***,two different deep learning models are presented to classify the *** multi-layers Convolution Neural Network(ML-CNN) and two stages Long Short Term Memory(2 s-LSTM) Network can achieve accuracy of 97.50% and 93.60% respectively,shows it is feasible to achieve the goal of personal *** the time cost of ML-CNN is higher than the 2 s-LSTM,both are lower than human reaction *** the architecture of ML-CNN is more suitable to achieving the goal of personal authentication.

关键词： Personal Authentication Surface Electromyography(sEMG) Myo multi-layers Convolution Neural Network(CNN) LSTM Network

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Monitoring and Forecasting Quality Indicators of Predough Production in the Bakery Industry 5

Monitoring and Forecasting Quality Indicators of Predough Pr...

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5th IEEE KhPI Week on Advanced Technology, KhPIWeek 2024

作者： Lutska, Nataliia Zaiets, Nataliia Vlasenko, Lidiia Zhyltsov, Andrii Dept. of Automation and Computer Technologies of Control Systems National University of Food Technologies Kyiv Ukraine dept. of Automation and Robotic Systems National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Dept. of Software Engineering and Cyber Security State University of Trade and Economics Kyiv Ukraine Dept. of Electromagnetic Systems The Institute of Electrodynamics The National Academy of Sciences of Ukraine Kyiv Ukraine

ISBN: (纸本)9798350384499

The work demonstrates the process of developing a machine learning model for a system for monitoring and controlling the quality of predough at a bakery. This system will provide continuous analysis of the predough parameters, such as temperature, humidity, lifting force and titranic acidity, which will ensure timely detection of deviations in the quality of the predough and avoid production problems. In addition, it will help automate the quality control process and ensure the stability of production processes. Analysis and forecasting of dough parameters will improve the quality of produced bread or other bakery products. Management based also on the predicted values of technological indicators of the predough will allow the enterprise to avoid unnecessary costs of materials and energy and increase economic efficiency. As part of the study, seven machine learning models were created and reviewed, including three linear and four varieties of binary decision trees. An analysis of the best model - a regression decision tree - was carried out, confirming its effectiveness and the validity of the resulting hierarchical structure, in particular, the prediction of important indicators of predough with a high degree of reliability, which indicates its importance in practical applications in production. The created model can be used to monitor and control product quality in real time, allowing operators to quickly identify and correct any deviations in process performance. Also, by analyzing changes in the variables of the predough production process, it is possible to identify precursors of possible production accidents or deviations in product quality, which will allow timely measures to be taken to avoid them. ©2024 IEEE.

关键词： Bakeries

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Analysis of coupled axial-torsional vibration of drill-string with an inclination angle 41

Analysis of coupled axial-torsional vibration of drill-strin...

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第41届中国控制会议

作者： Jiahao Zhang Chengda Lu Hengyu Huang Jun Gao Min Wu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education CCTEG Xi'an Research Institute

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Drill-string vibration has a great negative influence on the safety and efficiency of geological *** that the influence of drill-string inclination is not well considered in the literature,this paper develops a novel drill-string vibration model for geological drilling with inclined ***,the correlation between the inclination angle of borehole and the axial and torsional forces on the drill-string is *** on this,a drill-string motion model with the parameters of inclination angle is ***,the bit-rock interaction is considered as two processes,axial cutting and torsional friction,and an axial-torsional coupled bit-rock interaction model with state-dependent time delay is *** combining the established drill-string motion model and bit-rock interaction model,a coupled axial-torsional vibration model of drill-string in inclined borehole is obtained with the effect of borehole wall friction taken into *** drill-string vibration model proposed in this paper is more general,and includes the existing coupled drill-string vibration model of vertical borehole,which is closer to the actual situation.

关键词： drill-string vibration drill-string inclination bit-rock interaction

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Topology of Nash Equilibrium Set with Quadratic Vector Payoff Functions

Topology of Nash Equilibrium Set with Quadratic Vector Payof...

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American control Conference (ACC)

作者： Zehui Guo Tomohisa Hayakawa Department of Systems and Control Engineering Tokyo Institute of Technology Meguro Tokyo Japan

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

The condition when the Nash equilibrium set has a simple topological structure is presented. Specifically, we first define the terms ‘weakly simplicial’ and ‘simplicial’ for the Nash equilibrium set characterization problem (NESCP), which is a generalization of the terms for the Pareto optimality characterization problem. Then, we give a condition for when the NESCP is weakly simplicial so that the Nash equilibrium set is compact. After that, we present a condition for the NESCP to be simplicial, when each face of the simplices corresponds to a face of the Nash equilibrium set. Finally, we give a couple of examples to illustrate our results.

关键词： Buildings Games Nash equilibrium Rendering (computer graphics) Vectors Topology Faces

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Enabling Few-Shot Learning with PID control: A Layer Adaptive Optimizer 41

Enabling Few-Shot Learning with PID Control: A Layer Adaptiv...

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41st International Conference on Machine Learning, ICML 2024

作者： Yu, Le Li, Xinde Zhang, Pengfei Zhang, Zhentong Dunkin, Fir School of Automation Southeast University Nanjing China Nanjing Center for Applied Mathematics Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China Southeast University Shenzhen Research Institute Shenzhen China

Model-Agnostic Meta-Learning (MAML) and its variants have shown remarkable performance in scenarios characterized by a scarcity of labeled data during the training phase of machine learning models. Despite these successes, MAML-based approaches encounter significant challenges when there is a substantial discrepancy in the distribution of training and testing tasks, resulting in inefficient learning and limited generalization across domains. Inspired by classical proportional-integral-derivative (PID) control theory, this study introduces a Layer-Adaptive PID (LA-PID) Optimizer, a MAML-based optimizer that employs efficient parameter optimization methods to dynamically adjust task-specific PID control gains at each layer of the network, conducting a first-principles analysis of optimal convergence conditions. A series of experiments conducted on four standard benchmark datasets demonstrate the efficacy of the LA-PID optimizer, indicating that LA-PID achieves state-of-the-art performance in few-shot classification and cross-domain tasks, accomplishing these objectives with fewer training steps. Code is available on https://***/yuguopin/LA-PID. Copyright 2024 by the author(s)

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EDSA-Ensemble: An Event Detection Sentiment Analysis Ensemble Architecture

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IEEE Transactions on Affective Computing 2025年第2期16卷 555-572页

作者： Petrescu, Alexandru Truică, Ciprian-Octavian Apostol, Elena-Simona Paschke, Adrian National University of Science and Technology Politehnica Bucharest Computer Science and Engineering Department Faculty of Automatic Control and Computers Bucharest060042 Romania Academy of Romanian Scientists 3 Ilfov Bucharest Romania Freie Universitaet Berlin Fraunhofer Institute for Open Communication Systems Berlin14195 Germany Leipzig04109 Germany

As global digitization continues to grow, technology becomes more affordable and easier to use, and social media platforms thrive, becoming the new means of spreading information and news. Communities are built around sharing and discussing current events. Within these communities, users are enabled to share their opinions about each event. Using Sentiment Analysis to understand the polarity of each message belonging to an event, as well as the entire event, can help to better understand the general and individual feelings of significant trends and the dynamics on online social networks. In this context, we propose a new ensemble architecture, EDSA-Ensemble (Event Detection Sentiment Analysis Ensemble), that uses Event Detection and Sentiment Analysis to improve the detection of the polarity for current events from Social Media. For Event Detection, we use techniques based on Information Diffusion taking into account both the time span and the topics. To detect the polarity of each event, we preprocess the text and employ several Machine and Deep Learning models to create an ensemble model. The preprocessing step includes several word representation models: raw frequency, TFIDF, Word2Vec, and Transformers. The proposed EDSA-Ensemble architecture improves the event sentiment classification over the individual Machine and Deep Learning models. © 2010-2012 IEEE.

关键词： Sentiment analysis

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Machine Learning in Predicting the Impact of Filter Parameters on the Accuracy of Biosignal Measurement 27

Machine Learning in Predicting the Impact of Filter Paramete...

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27th International Conference on Digital Signal Processing and its Applications, DSPA 2025

作者： Altay, Yeldos A. Uskenbayeva, Raisa K. Ayazbay, Abu-Alim E. Fedorov, Alexey V. Department of Robotics and Technical Means of Automation Satbayev University Almaty Kazakhstan Institute of Automation and Information Technologies Vice-Rector Satbayev University Almaty Kazakhstan Almaty University of Power Engineering and Telecomunications Almaty Kazakhstan Faculty of Control Systems and Robotics ITMO University Saint-Petersburg Russian Federation

ISBN: (纸本)9798331518752

In this scientific article under consideration, a machine learning model has been developed that allows predicting the impact of filter parameters on the accuracy of measuring a biosignal - an ECG (electrocardiography) signal. For the first time, quantitative results have shown the degree of influence and the error introduced into the measured biosignal and described through dependence. The results of assessing the obtained relationship of indicators demonstrate an inverse correlation relationship that characterizes a decrease in the accuracy of measurement at the output of a high-order digital filtering system. The machine learning model is based on the linear regression method the dependence of which is approximated by the method based on least squares and visualized using a scattergram. The adequacy of the developed machine learning model was confirmed by calculating the coefficient of determination and checking its statistical significance. The developed model can be used to create new or improve existing biomedical data processing systems to increase the reliability of the results. © 2025 IEEE.

关键词： digital filters ECG signal processing filtering machine learning polynomial coefficients predicting

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Adaptive finite-time command filtered position control for DP ship in level ice 2

Adaptive finite-time command filtered position control for D...

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2024 2nd International Conference on Applied Statistics, Modeling and Advanced Algorithms, ASMA 2024

作者： Liu, Caiyun Shao, Chunrui Chen, Xinghua Liu, Qian Zheng, Zhenming College of Automation Harbin University of Science and Technology Heilongjiang Harbin150080 China College of Intelligent Systems Science and Engineering Harbin Engineering University Heilongjiang Harbin150001 China Beijing Institute of Control and Electronic Technology Beijing100000 China Zhejiang Huadong Geotechnical Investigation & Design Institute Co. Ltd. Zhejiang Hangzhou310030 China

This work suggests an adaptive limited-time command filtering control method for moving ships around in the Arctic. It does a good job of solving the thruster dynamics problem while taking into account uneven ice loads, model errors, and unknown changes in the environment. In the DP system, the neural network system is used to get close to the unclear function. A finite-time control law is meant to get the ship to the point and course that the captain wants by using estimates. Lyapunov analysis showed that the closed-loop system as a whole is stable, which means that all signals are still limited in time. Number-based simulations have shown that the suggested control strategy works. © Published under licence by IOP Publishing Ltd.

关键词： Adaptive filtering

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