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5th IEEE International Conference on Modern electrical and Energy System, MEES 2023

作者： Khrebtova, Oksana Zachepa, Iurii Zachepa, Nataliia Nekrasov, Andriy Pavlo, Kvitash Hrytsai, Oleksandr Kremenchuk Mykhailo Ostrohradskyi National University Department of Systems of Automatic Control and Electric Drive Kremenchuk Ukraine Kremenchuk Mykhailo Ostrohradskyi National University Electrical Engineering Kremenchuk Ukraine Kremenchuk Mykhailo Ostrohradskyi National University Department of Jurisprudence Sciences Kremenchuk Ukraine

ISBN: (纸本)9798350359787

Operational loads have both static and dynamic characteristics. Dynamic loads occur during the operation of the considered mechanism, both during acceleration and deceleration periods, as well as during steady motion due to the movement of the moving element along an uneven path caused by the presence of the working environment on the elements over which the filter-press plates are moving. The dynamic loading is significant and affects the formation of plate-side displacements during their movement while performing the technological operation. Experimental studies of the load on the movement elements were conducted to determine optimal control modes for the filter-press plate movement mechanism, aiming to avoid overloading during stopping and filter jamming. To analyze the loading, discretization of random processes of the filter movement mechanism loading was performed. The sequence of calculating the statistical characteristics of the schematized dynamic process is presented. Based on experimental data, mathematical calculation of the results of schematization and the type of probability distribution law was carried out. To select the law that best reflects the experimental data distribution of load amplitudes, the Kolmogorov-Smirnov goodness-of-fit criterion was applied. According to the calculation results, it was found that the Weibull distribution law adequately reflects the distribution of amplitudes since its corresponding Kolmogorov-Smirnov criterion value is the smallest. © 2023 IEEE.

关键词： Dynamic loads

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Disturbance Attenuation in the Euler–Bernoulli Beam with Viscous and Kelvin–Voigt Damping via Piezoelectric Actuators

Disturbance Attenuation in the Euler–Bernoulli Beam with Vi...

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IEEE Conference on Decision and control

作者： Anton Selivanov Emilia Fridman Department of Automatic Control and Systems Engineering The University of Sheffield UK School of Electrical Engineering Tel Aviv University Israel

We design a state-feedback controller, applied via piezoelectric actuators, that suppresses the effect of a distributed disturbance in the Euler-Bernoulli beam with viscous and Kelvin-Voigt damping. The controller is designed to improve performance on a finite number of modes. Its effect on the remaining (infinitely many) modes is analysed by constructing an appropriate Lyapunov functional, whose properties are guaranteed by the feasibility of linear matrix inequalities (LMIs). The LMIs allow us to design suitable controller gain and estimate the induced $L^2$ gain. A numerical example demonstrates how this modal decomposition approach leads to a controller that significantly reduces the $L^2$ gain.

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On output consensus of heterogeneous dynamical networks

arXiv

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arXiv 2024年

作者： Su, Yongkang Su, Lanlan Khong, Sei Zhen Department of Automatic Control & Systems Engineering University of Sheffield Sheffield United Kingdom Department of Electrical Engineering National Sun Yat-Sen University Kaohsiung80424 Taiwan

This work is concerned with interconnected networks with non-identical subsystems. We investigate the output consensus of the network where the dynamics are subject to external disturbance and/or reference input. For a network of output-feedback passive subsystems, we first introduce an index that characterises the gap between a pair of adjacent subsystems by the difference of their input-output trajectories. The set of these indices quantifies the level of heterogeneity of the networks. We then provide a condition in terms of the level of heterogeneity and the connectivity of the networks for ensuring the output consensus of the interconnected network. Copyright © 2024, The Authors. All rights reserved.

关键词： Heterogeneous networks

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Invention of Line-ChatBot: An Innovative Application of ChatGPT API and LINE Bot for Enhanced Student Learning

Invention of Line-ChatBot: An Innovative Application of Chat...

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IEEE International Conference on Knowledge Innovation and Invention (ICKII)

作者： Bing-Hong Chen Chih-Cheng Chen Electrical and Communications Engineering Feng Chia University Taiwan Department of Automatic Control Engineering Feng Chia University Taiwan

The intelligent teaching assistant system, Line-ChatBot based on the ChatGPT API and LINE Bot is used to for homework recommendations and learning guidance. The system uses a generative language model as an accessible and cost-effective learning support tool. It has been designed to effectively comprehend and decipher difficulties in doing homework and provides tailored suggestions and guidance. Overall, Line-ChatBot is a tool for aiding students in their learning by offering an efficient, flexible, and natural learning support system. We proposed the application of this system in educational contexts for the innovation and advancement of education.

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Operator Splitting for Convex Constrained Markov Decision Processes

arXiv

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arXiv 2024年

作者： Grontas, Panagiotis D. Tsiamis, Anastasios Lygeros, John Automatic Control Laboratory Department of Electrical Engineering and Information Technology ETH Zürich Physikstrasse 3 Zürich8092 Switzerland

We consider finite Markov decision processes (MDPs) with convex constraints and known dynamics. In principle, this problem is amenable to off-the-shelf convex optimization solvers, but typically this approach suffers from poor scalability. In this work, we develop a first-order algorithm, based on the Douglas-Rachford splitting, that allows us to decompose the dynamics and constraints. Thanks to this decoupling, we can incorporate a wide variety of convex constraints. Our scheme consists of simple and easy-to-implement updates that alternate between solving a regularized MDP and a projection. The inherent presence of regularized updates ensures last-iterate convergence, numerical stability, and, contrary to existing approaches, does not require us to regularize the problem explicitly. If the constraints are not attainable, we exploit salient properties of the Douglas-Rachord algorithm to detect infeasibility and compute a policy that minimally violates the constraints. We demonstrate the performance of our algorithm on two benchmark problems and show that it compares favorably to competing approaches. © 2024, CC BY.

关键词： Markov processes

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Mitigating Polarization in Recommender Systems via Network-aware Feedback Optimization

arXiv

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arXiv 2024年

作者： Chandrasekaran, Sanjay De Pasquale, Giulia Belgioioso, Giuseppe Dörfler, Florian The Automatic Control Laboratory Department of Electrical Engineering and Information Technology ETH Zürich Physikstrasse 3 Zürich8092 Switzerland

We consider a recommender system that takes into account the interaction between recommendations and the evolution of user interests. Users opinions are influenced by both social interactions and recommended content. We leverage online feedback optimization to design a recommender system that trades-off between maximizing engagement and minimizing polarization. The recommender system is agnostic about users’ opinion, clicking behavior, and social interactions, and solely relies on clicks. We establish optimality and closed-loop stability of the resulting feedback interconnection between the social platform and the recommender system. We numerically validate our algorithm when the user population follows an extended Friedkin–Johnsen model. We observe that network-aware recommendations significantly reduce polarization without compromising user engagement. © 2024, CC BY.

关键词： Convex optimization

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Energy performance of Internet of Things (IoT) networks for pipeline monitoring

Energy performance of Internet of Things (IoT) networks for ...

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Godlove Suila Kuaban Tadeusz Czachórski Erol Gelenbe Piotr Pecka Valery Nkemeni Piotr Czekalski Polish Academy of Sciences (IITiS PAN) Institute of Theoretical and Applied Informatics Gliwice Poland Laboratory of Electrical Engineering and Computing Faculty of Engineering and Technology University of Buea Cameroon Faculty of Automatic Control Electronics and Informatics Silesian University of Technology Gliwice Poland

ISBN: (数字)9798350361261

ISBN: (纸本)9798350361278

Pipelines are the most convenient ways to transport fluids (e.g., water, oil, and gas). However, leakage of fluids into the environment results in resource wastage (primarily water, which is becoming a scarce resource) and environmental pollution (in the case of leakage of toxic fluids like oil and gas). Emerging technologies like the Internet of Things (IoT), Wireless Sensor Networks (WSNs), Artificial Intelligence (AI), distributed computing, and cloud computing enable continuous monitoring of pipelines to detect leakages and corrosion on the pipeline. The main challenge with using battery-powered sensor nodes to monitor pipelines is the energy constraint, necessitating frequent battery replacement. Thus, there is a need to develop energy-saving mechanisms to prolong the lifetime of these sensor nodes. In this paper, we use the diffusion approximation modelling framework in which the data from the experimental testbed are used to model the dynamics of the battery’s energy content and to estimate the mean and variance of the device’s lifetime. The novelty in the proposed diffusion model of the battery of an IoT node is the introduction of multiple energy thresholds that split the energy state-space of the battery into multiple energy-saving regimes. As the battery discharges, the node gradually transitions into energy-saving regimes by reconfiguring some of its parameters to reduce energy consumption (sometimes at the cost of trading off some performance metrics). We investigate the impact of energy-saving regimes or the number of thresholds on the node’s lifetime.

关键词： Wireless sensor networks Fluids Pipelines Data models Water pollution Batteries Sensors

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Carbon-Aware Computing in a Network of Data Centers: A Hierarchical Game-Theoretic Approach

Carbon-Aware Computing in a Network of Data Centers: A Hiera...

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European control Conference (ECC)

作者： Enno Breukelman Sophie Hall Giuseppe Belgioioso Florian Dörfler Division of Decision and Control Systems KTH Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm Sweden Department of Electrical Engineering and Information Technology Automatic Control Laboratory ETH Zurich Zürich Switzerland

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Over the past decade, the continuous surge in cloud computing demand has intensified data center workloads, leading to significant carbon emissions and driving the need for improving their efficiency and sustainability. This paper focuses on the optimal allocation problem of batch compute loads with temporal and spatial flexibility across a global network of data centers. We propose a bilevel game-theoretic solution approach that captures the inherent hierarchical relationship between supervisory control objectives, such as carbon reduction and peak shaving, and operational objectives, such as priority-aware scheduling. Numerical simulations with real carbon intensity data demonstrate that the proposed approach success-fully reduces carbon emissions while simultaneously ensuring operational reliability and priority-aware scheduling.

关键词： Data centers Processor scheduling Computational modeling Carbon dioxide Games Supervisory control Resource management

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Risk-Aware Wasserstein Distributionally Robust control of Vessels in Natural Waterways

arXiv

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arXiv 2023年

作者： Nadales, Juan Moreno Hakobyan, Astghik de la Peña, David Muñoz Limon, Daniel Yang, Insoon The Department of Automatic Control and System Engineering University of Seville Spain The Department of Electrical and Computer Engineering Seoul National University Korea Republic of

In the realm of maritime transportation, autonomous vessel navigation in natural inland waterways faces persistent challenges due to unpredictable natural factors. Existing scheduling algorithms fall short in handling these uncertainties, compromising both safety and efficiency. Moreover, these algorithms are primarily designed for non-autonomous vessels, leading to labor-intensive operations vulnerable to human error. To address these issues, this study proposes a risk-aware motion control approach for vessels that accounts for the dynamic and uncertain nature of tide islands in a distributionally robust manner. Specifically, a model predictive control method is employed to follow the reference trajectory in the time-space map while incorporating a risk constraint to prevent grounding accidents. To address uncertainties in tide islands, a novel modeling technique represents them as stochastic polytopes. Additionally, potential inaccuracies in waterway depth are addressed through a risk constraint that considers the worst-case uncertainty distribution within a Wasserstein ambiguity set around the empirical distribution. Using sensor data collected in the Guadalquivir River, we empirically demonstrate the performance of the proposed method through simulations on a vessel. As a result, the vessel successfully navigates the waterway while avoiding grounding accidents, even with a limited dataset of observations. This stands in contrast to existing non-robust controllers, highlighting the robustness and practical applicability of the proposed approach. Copyright © 2023, The Authors. All rights reserved.

关键词： Stochastic systems

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Haptic object identification for advanced manipulation skills 9th

Haptic object identification for advanced manipulation skill...

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9th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2020

作者： Gabler, Volker Maier, Korbinian Endo, Satoshi Wollherr, Dirk Automatic Control Engineering Munich Germany Information Oriented Control Department of Electrical and Computer Engineering Technical University of Munich Munich Germany

ISBN: (纸本)9783030643126

In order to identify the characteristics of unknown objects, humans-in contrast to robotic systems-are experts in exploiting their sensory and motoric abilities to refine visual information via haptic perception. While recent research has focused on either estimating the geometry or material properties, this work strives to combine these aspects by outlining a probabilistic framework that efficiently refines initial knowledge from visual sensors by generating a belief state over the object shape while simultaneously learn material parameters. Specifically, we present a grid-based and a shape-based exploration strategy, that both apply the concepts of Bayesian-Filter theory in order to decrease the uncertainty. Furthermore, the presented framework is able to learn about the geometry as well as to distinguish areas of different material types by applying unsupervised machine learning methods. The experimental results from a virtual exploration task highlight the potential of the presented methods towards enabling robots to autonomously explore unknown objects, yielding information about shape and structure of the underlying object and thus, opening doors to robotic applications where environmental knowledge is limited. © Springer Nature Switzerland AG 2020.

关键词： Autonomous agents

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