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IEEE Conference on Decision and control

作者： Yorick Broens Hans Butler Roland Tóth Department of Electrical Engineering Eindhoven University of Technology Eindhoven The Netherlands ASML Veldhoven The Netherlands Systems and Control Laboratory HUNREN Institute for Computer Science and Control Hungary

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Motion systems are a vital part of many industrial processes. However, meeting the increasingly stringent demands of these systems, especially concerning precision and throughput, requires novel control design methods that can go beyond the capabilities of traditional solutions. Traditional control methods often struggle with the complexity and position-dependent effects inherent in modern motion systems, leading to compromises in performance and a laborious task of controller design. This paper addresses these challenges by introducing a novel structured feedback control auto-tuning approach for multiple-input multiple-output (MIMO) motion systems. By leveraging frequency response function (FRF) estimates and the linear-parameter-varying (LPV) control framework, the proposed approach automates the controller design, while providing local stability and performance guarantees. Key innovations include norm-based magnitude optimization of the sensitivity functions, an automated stability check through a novel extended factorized Nyquist criterion, a modular structured MIMO LPV controller parameterization, and a controller discretization approach which preserves the continuous-time (CT) controller parameterization. The proposed approach is validated through experiments using a state-of-the-art moving-magnet planar actuator prototype.

关键词： Technological innovation Sensitivity Frequency-domain analysis Stability criteria Prototypes Throughput Frequency response Motion control Optimization MIMO communication

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control Contraction Metrics on Submanifolds

Control Contraction Metrics on Submanifolds

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IEEE Conference on Decision and control

作者： Dongjun Wu Bowen Yi Ian R. Manchester Department of Automatic Control Lund University Box 118 Lund Sweden Department of Electrical Engineering & GERAD Polytechnique Montreal QC Canada Australian Centre for Robotics and School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney Australia

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this paper, we extend the control contraction metrics (CCM) approach, which was originally proposed for the universal tracking control of nonlinear systems, to those that evolves on submanifolds. We demonstrate that the search for CCM on submanifolds can be reformulated as convex conditions. In particular, since Lie groups can be viewed as submanifolds in Euclidean space, the results are directly applicable to this setting.

关键词： Measurement Lie groups Aerospace electronics control systems Nonlinear systems

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Differentially Private Online Federated Learning with Correlated Noise

arXiv

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arXiv 2024年

作者： Zhang, Jiaojiao Zhu, Linglingzhi Johansson, Mikael Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong

We introduce a novel differentially private algorithm for online federated learning that employs temporally correlated noise to enhance utility while ensuring privacy of continuously released models. To address challenges posed by DP noise and local updates with streaming non-iid data, we develop a perturbed iterate analysis to control the impact of the DP noise on the utility. Moreover, we demonstrate how the drift errors from local updates can be effectively managed under a quasi-strong convexity condition. Subject to an (ϵ, δ)DP budget, we establish a dynamic regret bound over the entire time horizon, quantifying the impact of key parameters and the intensity of changes in dynamic environments. Numerical experiments confirm the efficacy of the proposed algorithm. © 2024, CC BY.

关键词： Federated learning

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Medical Image Fusion in the NSST Domain with AR-Improved PA-PCNN 2022

Medical Image Fusion in the NSST Domain with AR-Improved PA-...

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4th International Conference on Intelligent Medicine and Image Processing, IMIP 2022

作者： Pei, Gaole Shi, T.A.O. Li, Shixing College of Electrical Engineering North China University of Science and Technology China Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems School of Electrical and Electronic Engineering Tianjin University of Technology China Department of Radiology Tianjin Beichen Hospital China

ISBN: (纸本)9781450396202

To present a medical image fusion method based on the non-subsampled shearlet transform (NSST) and improved parametric adaptive pulse-coupled neural network (PA-PCNN) for CT and MRI, which makes the fused images clearer and contains more information. The matched brain CT and MR-T2 are multi-scale decomposed by NSST, and the two source images are decomposed into low-frequency sub-bands and high-frequency sub-bands. The low-frequency fusion coefficients are obtained by fusing the low-frequency sub-band coefficients using the weighted sum-modified-Laplacian (WSML) low-frequency fusion rule. Meanwhile, the high-frequency sub-band coefficients are fused using the PA-PCNN model modified by the area ratio (AR) principle to obtain the high-frequency fusion coefficients. Finally, the low-frequency fusion coefficients and the high-frequency fusion coefficients are inverse transformed by NSST to obtain the final fused image. Compared to viewing CT or MR images alone, the fused images obviously display the relationship between soft mass and hard tissues. The fused image contains both the information of CT and MR. After fusion by the NSST-PA-AR-PCNN algorithm proposed in this paper, the details of the fused images are richer and the image quality is better than that of the previous fusion algorithms. This improved medical image fusion method of CT and MR could result that the final fused images are of higher quality to help detect anatomical structures and associated lesions in the brain. © 2022 ACM.

关键词： Magnetic resonance imaging

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Physical and Mathematical Modeling of Impedance-Based Fault Location Utilizing Synchrophasor Measurements 4

Physical and Mathematical Modeling of Impedance-Based Fault ...

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4th International Youth Scientific and Technical Conference Relay Protection and Automation, RPA 2021

作者： Yablokov, A.A. Ivanov, I.E. Tychkin, A.R. Kulikov, F.A. Murzin, A.Yu. Ivanovo State Power Engineering University Department of Electric Power Systems Automatic Control Ivanovo Russia Ivanovo State Power Engineering University Department of Electric Power Systems Ivanovo Russia

ISBN: (纸本)9781728192703

The focus of this paper is on the impedance-based transmission line fault location via synchronized phasor measurements. Physical and mathematical modeling involving real-time digital simulations is utilized to show that synchrophasor-based fault location is promising for extra-high voltage overhead transmission lines. A variety of single-end and double-end fault location methods are put together to show that the fault location accuracy can be well within 1-2 % for both P and M class filters defined in the IEEE C37.118 synchrophasor standard. The analysis is carried out for a reliable 750 kV line model built in the ATPDraw software along with an electric grid model with 500, 330, and 220 kV overhead lines sharing the same right-of-way. Unlike many other publications, no Fourier-simulated phasors under transients are exploited. Instead, we resort to physical modeling involving hardware equipped with synchrophasor functionality. An experimental setup is described, and future research directions are highlighted. © 2021 IEEE.

关键词： Location

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Robust control of Feeding Speed for Coal Mine Tunnel Drilling Machines 25

Robust Control of Feeding Speed for Coal Mine Tunnel Drillin...

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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Liu, Xiao Chen, Luefeng Wu, Min Cao, Weihua Lu, Chengda Pedrycz, Witold School of Automation China University of Geosciences Wuhan China School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration 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 Department of Computer Engineering Sariyer Istanbul34396 Turkey

Changes in coal seam hardness cause fluctuations in the feed resistance at the drill bit during the drilling process, leading to unstable feeding speed. This paper proposes a robust dynamic output feedback controller to suppress disturbances caused by the variations in coal seam hardness in the feed system. Firstly, an unknown parameter measuring coal seam hardness is introduced, and an uncertain model of the feeding system is established based on the finite element model of the drill string. By designing weighted functions based on industrial field requirements and constructing a generalized plant, the controller achieves loop shaping, reducing the low-frequency impact of coal seam hardness variations on the feed system and suppressing the systems resonance peak. Simulation results demonstrate that the controller effectively suppresses parameter variations and external disturbances caused by changes in coal seam hardness, achieving stable control of the drilling speed. © 2024 IEEE.

关键词： Robust control

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ON-Traffic: An Operator Learning Framework for Online Traffic Flow Estimation and Uncertainty Quantification from Lagrangian Sensors

arXiv

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arXiv 2025年

作者： Rap, Jake Das, Amritam Eindhoven University of Technology Department of Electrical Engineering Control Systems group P.O. Box 513 Eindhoven5600 MB Netherlands

Accurate traffic flow estimation and prediction are critical for the efficient management of transportation systems, particularly under increasing urbanization. Traditional methods relying on static sensors often suffer from limited spatial coverage, while probe vehicles provide richer, albeit sparse and irregular data. This work introduces ON-Traffic, a novel deep operator Network and a receding horizon learning-based framework tailored for online estimation of spatio-temporal traffic state along with quantified uncertainty by using measurements from moving probe vehicles and downstream boundary inputs. Our framework is evaluated in both numerical and simulation datasets, showcasing its ability to handle irregular, sparse input data, adapt to time-shifted scenarios, and provide well-calibrated uncertainty estimates. The results demonstrate that the model captures complex traffic phenomena, including shockwaves and congestion propagation, while maintaining robustness to noise and sensor dropout. These advancements present a significant step toward online, adaptive traffic management systems. Copyright © 2025, The Authors. All rights reserved.

关键词： Information management

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MaxCUCL: Max−Consensus with Deterministic Convergence in Networks with Unreliable Communication Links

arXiv

引用

arXiv 2024年

作者： Rikos, Apostolos I. Charalambous, Themistoklis Johansson, Karl H. Department of Electrical and Computer Engineering Division of Systems Engineering Boston University Boston United States Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Division of Decision and Control Systems KTH Royal Institute of Technology also affiliated with Digital Futures StockholmSE-100 44 Sweden

In this paper, we present a novel distributed algorithm (herein called MaxCUCL) designed to guarantee that max−consensus is reached in networks characterized by unreliable communication links (i.e., links suffering from packet drops). Our proposed algorithm is the first algorithm that achieves max−consensus in a deterministic manner (i.e., nodes always calculate the maximum of their states regardless of the nature of the probability distribution of the packet drops). Furthermore, it allows nodes to determine whether convergence has been achieved (enabling them to transition to subsequent tasks). The operation of MaxCUCL relies on the deployment of narrowband error-free feedback channels used for acknowledging whether a packet transmission between nodes was successful. We analyze the operation of our algorithm and show that it converges after a finite number of time steps. Finally, we demonstrate our algorithm’s effectiveness and practical applicability by applying it to a sensor network deployed for environmental monitoring. © 2024, CC BY.

关键词： Probability distributions

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Fractional order MRAC control design for a lightning system based on a fractional order second degree model

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IFAC-PapersOnLine 2024年第12期58卷 95-100页

作者： Samir Ladaci Seif Eddine Khelas Amani R Ynineb Dana Copot Clara-Mihaela Ionescu Ecole Nationale Polytechnique Depart. Automatic Control Eng. El Harrach 16200 Algiers Algeria National Polytechnic School of Constantine E.E.A. Department 25100 Constantine Algeria Research Group on Dynamical Systems and Control Department of Electromechanical Systems and Metal Engineering Ghent University B-9052 Ghent Belgium

This paper presents a new adaptive fractional-order MRAC controller design for the class of non-integer second-order systems. The update of the control law gains follows a derivative of fractional order equal to the order of the controlled system model. The stability analysis of the control system has been performed based on Lyapunov theorem. We apply this control law to an experimental multivariable lightning system. The results obtained show the efficiency and performance improvement of the proposed control solution compared to the classical MRAC.

关键词： Fractional order system adaptive control MRAC FOMRAC Lightning system

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A Survey on Application of Artificial Intelligence Techniques in Microgrid control

A Survey on Application of Artificial Intelligence Technique...

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Compatibility in Power Electronics (CPE)

作者： Javier Gutiérrez-Escalona Carlos Roncero-Clemente Oleksandr Husev Eva González-Romera María Isabel Milanés-Montero Tomislav Dragičević Electrical Electronic and Control Engineering Department University of Extremadura Badajoz Spain Department of Electrical Power Engineering and Mechatronics Tallin University of Technology Tallin Estonia Wind and Energy Systems Department Technical University of Denmark (DTU) Copenhaguen Denmark

ISBN: (数字)9798350318265

ISBN: (纸本)9798350318272

Concerns over the energy and environmental crisis are driving the strategic integration of distributed generators (DGs) in power systems, hastening the shift to sustainable energy. Microgrids (MGs) emerged as self-reliant, localized power solutions for DGs integration, enhancing grid performance and reliability by allowing grid-connected and islanded modes of operation. Moreover, the dc nature of many DGs and household devices, together with the progress in power electronics, have shifted research from conventional ac MGs towards dc and hybrid ac/dc MGs, which increase the complexity and the number of control scenarios. Therefore, the MG control environment require advanced data-driven algorithms to overcome the stochasticity and non-linear characteristics of MGs systems. In this context, artificial intelligence (AI) techniques demonstrate high potential for enhancing the control and operation in the dynamic MG environment. This paper reviews the most recent research effort regarding the application of AI-based technology in the hierarchical control structure for ac, dc and hybrid ac/dc MG architectures.

关键词： Surveys Reviews Heuristic algorithms Refining Microgrids Propulsion Power electronics

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