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2023 International Conference on Power, Energy and Innovations, ICPEI 2023

作者： Sakulphaisan, Guntinan Son-In, Sirirat Junhuathon, Nitikorn Muankhaw, Theerapol Pathumwan Institute of Technology Faculty of Science and Technology Industrial Technology and Innovation Management Bangkok Thailand Bansomdejchaopraya Rajabhat University Faculty of Engineering and Industrial Technology Electrical Engineering and Automation Control Systems Bangkok Thailand Rajamangala University of Technology Faculty of Engineering Department of Electrical Engineering Thanyaburi Pathumthani Thailand

ISBN: (纸本)9798350344585

This study conducts a comprehensive analysis of optimizing the speed profile of an AE-bus, a critical step in enhancing its operational efficiency. It encompasses three distinct case studies, each targeting specific objectives. The first case emphasizes energy consumption reduction, contributing to overall resource efficiency. The second focuses on eco-conscious speed profiles within predefined travel durations, balancing environmental sustainability and timeliness. The third case prioritizes travel time minimization for streamlined efficiency. Detailed insights into speed adjustments, bus positions, and energy consumption patterns are provided for each case. The findings reveal tailored approaches for energy conservation, speed, and travel time optimization. Additionally, emissions analysis demonstrates that electric buses significantly reduce CO2 emissions compared to conventional NGV buses, showcasing their potential for environmental benefits. © 2023 IEEE.

关键词： Electric buses

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Maximizing social power in multiple independent Friedkin-Johnsen models

Maximizing social power in multiple independent Friedkin-Joh...

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European control Conference (ECC)

作者： Lingfei Wang Yu Xing Claudio Altafini Karl H. Johansson Division of Decision and Control Systems Digital Futures School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Electrical Engineering Division of Automatic Control Linköping University Linköping Sweden

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This paper investigates the problem of maximizing social power for a group of agents, who participate in multiple meetings described by independent Friedkin-Johnsen models. A strategic game is obtained, in which the action of each agent (or player) is her stubbornness over all the meetings, and the payoff is her social power on average. It is proved that, for all but some strategy profiles on the boundary of the feasible action set, each agent's best response is the solution of a convex optimization problem. Furthermore, even with the non-convexity on boundary profiles, if the underlying networks are given by a fixed complete graph, the game has a unique Nash equilibrium. For this case, the best response of each agent is analytically characterized, and is achieved in finite time by a proposed algorithm.

关键词： Network topology Europe Games Nash equilibrium Cost function Convex functions

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The ChatGPT After: Building Knowledge Factories for Knowledge Workers with Knowledge Automation

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IEEE/CAA Journal of automatica Sinica 2023年第11期10卷 2041-2044页

作者： Yutong Wang Xiao Wang Xingxia Wang Jing Yang Oliver Kwan Lingxi Li Fei-Yue Wang State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China School of Artificial Intelligence Anhui UniversityHefei 230039China Motion G Inc068898Singapore Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University IndianapolisIndiana 46202-5132 USA IEEE

Briefing: This perspective introduces the concept and framework of knowledge factories with knowledge machines for knowledge workers to achieve knowledge automation for Industry 5.0 and intelligent *** The big hit of Chat GPT makes it imperative to contemplate the practical applications of big or foundation models [1]-[5]. However, as compared to conventional models, there is now an increasingly urgent need for foundation intelligence of foundation models for real-world industrial applications.

关键词： Automation template Chat GPT

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MOVING HIGHER-ORDER TAYLOR APPROXIMATIONS METHOD FOR SMOOTH CONSTRAINED MINIMIZATION PROBLEMS

arXiv

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arXiv 2024年

作者： Nabou, Yassine Necoara, Ion Automatic Control and Systems Engineering Department University Politehnica Bucharest Romania Automatic Control and Systems Engineering Department University Politehnica Bucharest Gheorghe Mihoc - Caius Iacob Institute of Mathematical Statistics and Applied Mathematics The Romanian Academy Bucharest Romania

In this paper, we develop a higher-order method for solving composite (non)convex minimization problems with smooth (non)convex functional constraints. At each iteration, our method approximates the smooth part of the objective function and of the constraints by higher-order Taylor approximations, leading to a moving Taylor approximation method (MTA). We present convergence guarantees for the MTA algorithm for both, nonconvex and convex problems. In particular, when the objective and the constraints are nonconvex functions, we prove that the sequence generated by MTA algorithm converges globally to a KKT point. Moreover, we derive convergence rates in the iterates when the problem’s data satisfy the Kurdyka-Lojasiewicz (KL) property. Further, when the objective function is (uniformly) convex and the constraints are also convex, we provide (linear/superlinear) sublinear convergence rates for our algorithm. Finally, we present an efficient implementation of the proposed algorithm and compare it with existing methods from the literature. © 2024, CC BY.

关键词： Approximation algorithms

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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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Iterative Reference Learning for Cartesian Impedance control of Robot Manipulators

Iterative Reference Learning for Cartesian Impedance Control...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Julian M. Salt Ducaju Björn Olofsson Rolf Johansson Department of Automatic Control LTH Lund University Lund Sweden Department of Electrical Engineering Division of Vehicular Systems Linköping University Linköping Sweden

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In this paper, an iterative learning strategy was developed to improve trajectory tracking for an impedance-controlled robot manipulator. In this learning strategy, an update law was proposed to modify the Cartesian reference of an impedance controller. Also, the conditions that ensure its convergence considering the dynamics of the robot were derived. Finally, an experimental evaluation was performed using a Franka Emika Panda robot in two different robot tasks, and its results showed that robot task completion was achieved in a lower number of iterations, while maintaining a smooth physical interaction between the robot and its surroundings.

关键词： Trajectory tracking Collaborative robots Iterative methods Impedance Robots Manipulator dynamics Intelligent robots Convergence

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control of Isolated AC Microgrids with Constant Power Loads: A Set Invariance Approach

Control of Isolated AC Microgrids with Constant Power Loads:...

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Mediterranean Conference on control and Automation (MED)

作者： Grigoris Michos George C. Konstantopoulos Paul A. Trodden Visakan Kadirkamanathan Department of Automatic Control & Systems Engineering University of Sheffield Mappin Street Sheffield UK Department of Electrical and Computer Engineering University of Patras Rion Greece

This paper proposes a robust control scheme for isolated AC Microgrids, where each node is connected locally to a constant power load (CPL). Contrary to many approaches in the literature, we consider the explicit model of the inverter dynamics and separate the overall system into two parts; a nominal subsystem parametrized by a nominal load and an error subsystem describing the difference between the true and the nominal voltage, resulting from perturbations of the load demand. In the presented analysis, we investigate the non-linear structure of the CPL in order to analytically describe its geometric effect on the network dynamics. We exploit this information to propose mild conditions on the tuning parameters such that a positive invariant set for the error dynamics exists and the distance between the true and the nominal voltage trajectories is bounded at all times. We demonstrate the properties of the proposed control scheme in a simulated scenario.

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Neurophysiological Test with Use of EEG, GSR and Pulse Measurements Data for Focus Group Beverage Preference Aggregation 11

Neurophysiological Test with Use of EEG, GSR and Pulse Measu...

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11th International Scientific Conference on Computer Science, COMSCI 2023

作者： Andonov, Stanimir Georgiev, Stiliyan Tsenov, Georgi Mladenov, Valeri Management Faculty Technical University Economics Industrial Engineering and Managemen Department Sofia Bulgaria Validation - Vision Analysis Team Visteon Electronics Bulgaria Sofia Bulgaria Automatic Control Faculty Technical University Fundamentals of Theoretical Electrical Engineering Department Sofia Bulgaria

ISBN: (纸本)9798350325256

The primary objective in this case study is introduction of a testing methodology framework for assessing the effectiveness of different drinks and flavors through neuromarketing. The framework involves use of focus groups for evaluation of the neurophysiological reactions of participants to various stimuli and drawing statistically significant conclusions based on the results. In the last past decade, there has been an increase in the availability of affordable and easy-to-use biosensors that provides the possibility for affordable and easy to use real-time measurements of bio-signals, such as electroencephalography (EEG), galvanic skin response (GSR), and pulse. Also, with the recent ongoing increase of the computational capabilities the signal processing and analysis of the recorded biometric data can also be processed in real-time with relatively affordable and mobile hardware. By analyzing these signals and identifying an informative features that are derived statistically from group averaging and independent of individual user's deviations, it is possible to classify and then apply the measured brainwaves and other biometrics data in various applications. In this paper, the authors apply data from voltage potential electrodes EEG brainwaves, along with GSR and pulse in order to recognize the variation response levels among a sample focus group and the results for determination of their aggregated preferences on tested sample drinks. © 2023 IEEE.

关键词： Electroencephalography

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automatic Generation of Examinations in the automatic control Courses: Decision Support Matlab/L A TEX Toolkit for Stepwise Constructive Alignment ⁎

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IFAC-PapersOnLine 2024年第16期58卷 47-52页

作者： Alexander Stotsky Torsten Wik Division of Systems & Control Department of Electrical Engineering Chalmers University of Technology SE-412 96 Gothenburg Sweden

Final written examination is the most important part of summative assessment in automatic control courses. Preparation of the examinations with a given number of points according to the concept of Constructive Alignment (which could be the main concept in future automatic control education) takes significant amount of time of the educator and motivates development of a toolkit for automatic compilation of examination problems. A decision support Matlab/L A TEX toolkit based on random number generators for selection of examination problems is proposed in this paper to facilitate the alignment. The toolkit allows application of Stepwise Constructive Alignment (a new method proposed in this paper), where the alignment is achieved by a number of software runs associated with random trials. In each step the educator manually selects suitable problems before each run based on evaluation of the random choice from the previous run. automatic generation of the examination together with solutions for the course ‘Process control and measurement techniques’ is presented as an example.

关键词： Constructive Alignment in automatic control Education Computer Aided Development of Educational Materials automatic Generation of Examinations with Desired Indices of Difficulty Stepwise Constructive Alignment Decision Support Matlab/L A T E X Toolkit

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Deep learning framework for wind speed prediction in Saudi Arabia

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Neural Computing and Applications 2025年第5期37卷 3685-3701页

作者： Alabdulhadi, Arwa Ahmed Rehman, Shafiqur Ali, Amjad Shafiullah, Md Physics Department College of Science and Humanities Imam Abdulrahman Bin Faisal University Jubail3065 Saudi Arabia Interdisciplinary Research Center for Sustainable Energy Systems King Fahd University of Petroleum & Minerals Dhahran31261 Saudi Arabia Control & Instrumentation Engineering Department King Fahd University of Petroleum & Minerals Dhahran31261 Saudi Arabia Electrical Engineering Department King Fahd University of Petroleum & Minerals Dhahran31261 Saudi Arabia

Increased utilization of conventional energy sources severely impacts the environment by increasing the global temperature and contributing to global warming. Sustainable energy sources could contribute to handling the increment while also providing cheap, clean, and abundant energy. Wind energy is considered one of the most reliable sources of sustainable energy due to its abundance and availability during the day and night compared to other renewable resources. However, effective forecasting of such intermittent resources is considered a key challenge for power system operators. This paper develops a novel deep learning framework for forecasting the wind speed in Dhahran City, Saudi Arabia, using two years of data acquired at different heights from the light detection and ranging device, an active remote sensing wind monitoring system. It also segments the data and removes wrong measurements through data pre-processing. The article identifies the best configuration for deep learning models, such as long short-term memory, through a systematic approach. The presented results confirm the efficacy of the developed models against the selected statistical performance measures. The developed model performs better with large data volumes than with lower volumes. Finally, the comparative analysis with the literature-reported results provides confidence in the competency of the proposed model in predicting wind speed for various periods. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Clean energy

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