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International Conference on Electrical and Electronics Engineering, ELECO

作者： Zhengui Song Gyorgyi Dimirkovsky Jun Zhao Institute of Integrated Process Automation College of Information Science & Engineering Northeastern University Shenyang Liaoning China Institute of Automation & Systems Engineering Faculty of Electrical Engineering & Information Technologies Ss Cyril and Methodius University Skopje Macedonia Departments of Computer Engineering & Control Engineering Faculty of Engineering Dogus University Kadikoy Istanbul Turkey

Robust H ∞ output feedback control problem for a class of switched linear discrete-time systems possessing norm-bounded uncertainty and time-varying delay is investigated. A switched dynamic output feedback controller is sought that can robust exponentially stabilize and reduce to a prescribed level the effect of disturbance input on the controlled output in the closed loop. A delay-dependent linear matrix inequality based sufficient condition for the problem to be solvable is derived via the switched Lyapunov functions. controller design is performed by solving a set of linear matrix inequalities. An illustrative example along with simulation results is given to demonstrate the validity of these novel derivations.

关键词： Switches Robustness Output feedback Linear matrix inequalities Switched systems Delay

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Charged Particle Location Modeling Based Experiment Plan Acquisition Method

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Procedia computer science 2017年 104卷 592-597页

作者： Normunds Kante Mykola Kryshchuk Jurijs Lavendels Riga Technical University Faculty of Computer Science and Information Technology Kaļķu street 1 Rīga LV – 1658 Latvia National Technical University of Ukraine (Kiev Polytechnic Institute) Department of Automation and Control in Technical Systems 37 Prospect Peremogy Kiev 03056 Ukraine

The method of obtaining the plan of experiments in multidimensional space is proposed. Our method is based on assumptions of uniform distribution of charged particles in infinite space. To receive the plan of experiments, the infinite multidimensional space is replaced with a hypercube whose surface models influence of infinite space. The software is developed and practical results, in two-dimensional space are acquired. There are no basic problems to carry out calculations in multidimensional space.

关键词： Experiment plan Charged particle interaction Latin hypercube

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Sliding mode control of switched uncertain linear systems: Designing robust H∞ sliding surface

Sliding mode control of switched uncertain linear systems: D...

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International Conference on Electrical and Electronics Engineering, ELECO

作者： Jie Lian Gyorgyi Dimirkovsky Jun Zhao Institute of Integrated Process Automation College of Information Science & Engineering Northeastern University Shenyang Liaoning China Institute of Automation & Systems Engineering Faculty of Electrical Engineering & Information Technologies Ss Cyril and Methodius University Skopje Macedonia Departments of Computer Engineering & Control Engineering Faculty of Engineering Dogus University Kadikoy Istanbul Turkey

The robust H ∞ control problem for a class of uncertain switched linear systems by using the variable structure control is investigated. A robust H ∞ single sliding surface is shown to exist as long as a convex combination of the subsystems of the switched system is robustly stabilizable with disturbance attenuation level γ. A switching law is constructed via the single Lyapunov function technique. Variable structure controllers of subsystems are designed so as the resulting closed-loop system guarantees the robust H ∞ performance. An illustrative example and simulation results are given to demonstrate the effectiveness of the proposed design method.

关键词： Switches Switched systems Robustness Linear systems Attenuation Uncertain systems

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Efficient Time-Delay System Optimization with Auto-Configured Metaheuristics

Efficient Time-Delay System Optimization with Auto-Configure...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Roman Senkerik Aleksander Byrski Hubert Guzowski Peter Janku Tomas Kadavy Zuzana Kominkova Oplatkova Radek Matusu Michal Pluhacek Libor Pekar Maciej Smolka Adam Viktorin Department of Informatics and Artificial Intelligence A.I. Lab Faculty of Applied Informatics Tomas Bata University in Zlin Czech Republic Department of Automation and Control Engineering Faculty of Applied Informatics Tomas Bata University in Zlin Czech Republic Institute of Computer Science AGH University of Science and Technology Krakow Poland

This paper presents an experimental study that compares the performance of four selected metaheuristic algorithms for optimizing a time delay system model. Time delay system models are complex and challenging to optimize due to their inherent characteristics, such as non-linearity, multi-modality, and constraints. The study includes an explanation of the choice and core functionality of the selected algorithms, which are both baseline and state-of-the-art variants of self-organizing migrating algorithm (SOMA), state-of-the-art variant from the Success-History-based Adaptive Differential Evolution family of algorithms, with emphasis on diverse search (DISH algorithm), and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm. The hyperparameters of the metaheuristic algorithms were set using the iRace automatic algorithm configuration framework. The paper emphasizes the importance of metaheuristic algorithms in control engineering for time-delay systems to develop more effective and efficient control strategies and precise model identifications. The experimental results highlight the effectiveness of the state-of-the-art algorithms with specific adaptive mechanisms like population organization process, diverse search and adaptation mechanisms ensuring a gradual transition from exploration to exploitation. Overall, this study contributes to understanding the challenges and advantages of using metaheuristic algorithms in control engineering for time delay systems. The results provide valuable insights into the performance of modern metaheuristic algorithms and can help guide the selection of appropriate adaptive mechanisms of metaheuristics.

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Use of accelerometers for material inner defect detection

Use of accelerometers for material inner defect detection

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International Conference on Applied Electronics, AE

作者： Ondrej Krejcar Robert Frischer Department of Measurement and Control Center of Applied Cybernetics Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava Ostrava Czech Republic Department of Automation and Computing in Metallurgy VSB-Technical University of Ostrava Ostrava Czech Republic

This paper deals with a possibility of non-destructive diagnostics of solid objects by software analysis of vibration spectrum by accelerometers. By a use of MATLAB platform, a processing and information evaluation from accelerometer is possible. Accelerometer is placed on the measured object. The analog signal needs to be digitized by a special I/O device to be processed offline with FFT (Fast Fourier Transformation). The power spectrum is then examined by developed evaluating procedures.

关键词： Accelerometers Vibrations Software Conferences Distortion measurement Converters Unified modeling language

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Texture Analysis of Breast US Images Using Morphological Transforms, Hausdorff Dimension and Bagging Ensemble Method

Texture Analysis of Breast US Images Using Morphological Tra...

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Mediterranean Conference on control and automation (MED)

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 Romania Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics “Dunarea de Jos” University of Galati The Modelling & Simulation Laboratory Dunarea de Jos University of Galati Galati Romania

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

In this work, an attempt is made for the first time to use the measurement pattern generated by morphological transformation quantified by Hausdorff fractal dimension (HFD) and classified with ensemble learning based on bagging. The proposed work uses three morphological transformations for image preprocessing: hit-and-miss transform (HMT), white (WHT), and black top-hat (BHT). The pattern texture of US breast images is described by extracting the HFD from the regions of interest (ROI) after the ultrasound (US) images have been preprocessed. The main objective of this study was achieved by comparatively analyzing the classification performance of features using the Random Forest (RF), Extra Trees (ET) classifier, and bagging ensemble method based on XGBoot classifier. In presented study, the XGBoost classifier and BHT image processing method give an accuracy of 89.8% in a binary classification, benign versus malignant breast cancer.

关键词： Ultrasonic imaging Transforms Feature extraction Time measurement Fractals Ensemble learning Image preprocessing

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Clock Synchronization for Wireless Sensor Network with Communication Delay

Clock Synchronization for Wireless Sensor Network with Commu...

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American control Conference

作者： Emanuele Garone Andrea Gasparri Francesco Lamonaca Faculty of Applied Science Control and Systems Analysis Department Université Libre de Bruxelles 1050 Brussels Belgium Department of Computer Science and Automation University of "Roma Tre" Via della Vasca Navale 79 00146 Rome Italy Dept. of Electronic Systems and Computer Science University of Calabria Ponte Pietro Bucci 87040 Rende (CS)

ISBN: (纸本)9781479901777

In this work, the clock synchronization problem for wireless sensor networks is addressed. In our scenario, we consider a wireless sensor network where nodes are equipped with a local clock hardware and communicate in order to achieve a common sense of time. This work introduces a novel synchronization algorithm able to ensure a good level of synchronization even in the presence of random bounded communication delays. A theoretical analysis of the robustness of the proposed algorithm is proposed along with simulations to corroborate the theoretical finding.

关键词： Communication Delay clock synchronization theoretical finding

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Notice of Retraction: Material inner defect detection by a vibration spectrum analysis

Notice of Retraction: Material inner defect detection by a v...

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International Conference on Mechanical and Electronics Engineering (ICMEE)

作者： Ondrej Krejcar Robert Frischer Department of Measurement and Control Center for Applied Cybernetics Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava Ostrava Czech Republic Department of Automation and Computing in Metallurgy VSB-Technical University of Ostrava Ostrava Czech Republic

This article has been retracted by the publisher.

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Language-Conditioned Affordance-Pose Detection in 3D Point Clouds

arXiv

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arXiv 2023年

作者： Nguyen, Toan Vu, Minh Nhat Huang, Baoru Van Vo, Tuan Truong, Vy Le, Ngan Vo, Thieu Le, Bac Nguyen, Anh FPT Software AI Center Viet Nam Automation & Control Institute TU Wien Vienna Austria Imperial College London United Kingdom Department of Computer Science & Computer Engineering University of Arkansas United States Faculty of Mathematics and Statistics Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Computer Science University of Science Viet Nam Department of Computer Science University of Liverpool United Kingdom

Affordance detection and pose estimation are of great importance in many robotic applications. Their combination helps the robot gain an enhanced manipulation capability, in which the generated pose can facilitate the corresponding affordance task. Previous methods for affodance-pose joint learning are limited to a predefined set of affordances, thus limiting the adaptability of robots in real-world environments. In this paper, we propose a new method for language-conditioned affordance-pose joint learning in 3D point clouds. Given a 3D point cloud object, our method detects the affordance region and generates appropriate 6-DoF poses for any unconstrained affordance label. Our method consists of an open-vocabulary affordance detection branch and a language-guided diffusion model that generates 6-DoF poses based on the affordance text. We also introduce a new high-quality dataset for the task of language-driven affordance-pose joint learning. Intensive experimental results demonstrate that our proposed method works effectively on a wide range of open-vocabulary affordances and outperforms other baselines by a large margin. In addition, we illustrate the usefulness of our method in real-world robotic applications. Our code and dataset are publicly available at https://***. © 2023, CC BY-NC-SA.

关键词： Robotics

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DeepRicci: Self-supervised Graph Structure-Feature Co-Refinement for Alleviating Over-squashing

DeepRicci: Self-supervised Graph Structure-Feature Co-Refine...

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IEEE International Conference on Data Mining (ICDM)

作者： Li Sun Zhenhao Huang Hua Wu Junda Ye Hao Peng Zhengtao Yu Philip S. Yu School of Control and Computer Engineering North China Electric Power University Beijing China School of Computer Science Beijing University of Posts and Telecommunications Beijing China State Key Laboratory of Software Development Environment Beihang University Beijing China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China Department of Computer Science University of Illinois at Chicago IL USA

Graph Neural Networks (GNNs) have shown great power for learning and mining on graphs, and Graph Structure Learning (GSL) plays an important role in boosting GNNs with a refined graph. In the literature, most GSL solutions either primarily focus on structure refinement with task-specific supervision (i.e., node classification), or overlook the inherent weakness of GNNs themselves (e.g., over-squashing), resulting in suboptimal performance despite sophisticated designs. In light of these limitations, we propose to study self-supervised graph structure-feature co-refinement for effectively alleviating the issue of over-squashing in typical GNNs. In this paper, we take a fundamentally different perspective of the Ricci curvature in Riemannian geometry, in which we encounter the challenges of modeling, utilizing and computing Ricci curvature. To tackle these challenges, we present a self-supervised Riemannian model, DeepRicci. Specifically, we introduce a latent Riemannian space of heterogeneous curvatures to model various Ricci curvatures, and propose a gyrovector feature mapping to utilize Ricci curvature for typical GNNs. Thereafter, we refine node features by geometric contrastive learning among different geometric views, and simultaneously refine graph structure by backward Ricci flow based on a novel formulation of differentiable Ricci curvature. Finally, extensive experiments on public datasets show the superiority of DeepRicci, and the connection between backward Ricci flow and over-squashing. Codes of our work are given in https://***/RiemanGraph/.

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