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6th International Conference on Robotics and Automation in Industry, ICRAI 2024

作者： Ullah, Hameed Zarin, Owais Ahmad, Irfan Ahmad, Sarfraz Abbas, Ansar Lippiello, Vincenzo University of Naples Federico II Department of Electrical Engineering and Information Technology Naples Italy Riphah International University Department of Electrical Engineering Islamabad Pakistan School of Bilbao - EIB/BIE University of the Basque Country - UPV/EHU Automatic Control Group ACG Department of Automatic Control and Systems Engineering Rafael Moreno 3 Bilbao48013 Spain CEME Department of Electrical Engineering Islamabad Pakistan

ISBN: (纸本)9798350355703

This research presents a comprehensive analysis of quadrotor stabilization and trajectory tracking control using Proportional-Integral-Derivative (PID) and Sliding Mode control (SMC) with integrated disturbance rejection. The nonlinear dynamics of the quadrotor are formulated using the Newton-Euler approach, accounting for six degrees of freedom. The PID controller is implemented as a baseline, while the SMC is designed for enhanced robustness to model uncertainties and external perturbations, with a disturbance observer for managing time-varying disturbances. A rigorous Lyapunov stability proof ensures global asymptotic stability of the SMC-controlled system. Extensive simulations evaluate both controllers in terms of tracking accuracy, control effort, and robustness to external disturbances. Results show that SMC outperforms PID in dis-turbance rejection, tracking accuracy, and robustness, making it ideal for UAV applications in complex environments. © 2024 IEEE.

关键词： Sliding mode control

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Hybrid Optimization Algorithm for Handwritten Document Enhancement

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Computers, Materials & Continua 2024年第3期78卷 3763-3786页

作者： Shu-Chuan Chu Xiaomeng Yang Li Zhang Václav Snášel Jeng-Shyang Pan College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao266590China School of Information and Control Engineering Qingdao University of TechnologyQingdao266520China Faculty of Electrical Engineering and Computer Science VŠB-TU OstravaOstrava70080Czech Republic Department of Information Management Chaoyang University of TechnologyTaichung41349Taiwan

The Gannet Optimization Algorithm (GOA) and the Whale Optimization Algorithm (WOA) demonstrate strong performance;however, there remains room for improvement in convergence and practical applications. This study introduces a hybrid optimization algorithm, named the adaptive inertia weight whale optimization algorithm and gannet optimization algorithm (AIWGOA), which addresses challenges in enhancing handwritten documents. The hybrid strategy integrates the strengths of both algorithms, significantly enhancing their capabilities, whereas the adaptive parameter strategy mitigates the need for manual parameter setting. By amalgamating the hybrid strategy and parameter-adaptive approach, the Gannet Optimization Algorithm was refined to yield the AIWGOA. Through a performance analysis of the CEC2013 benchmark, the AIWGOA demonstrates notable advantages across various metrics. Subsequently, an evaluation index was employed to assess the enhanced handwritten documents and images, affirming the superior practical application of the AIWGOA compared with other algorithms.

关键词： Metaheuristic algorithm gannet optimization algorithm hybrid algorithm handwritten document enhancement

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Methods for the Efficient Energy management in a Smart Mini Greenhouse

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Computers, Materials & Continua 2022年第2期70卷 3169-3187页

作者： Vasyl Teslyuk Ivan Tsmots Michal Gregus ml. Taras Teslyuk Iryna Kazymyra Department of Automated Control Systems Lviv Polytechnic National UniversityLviv79013Ukraine Faculty of Management Comenius University in BratislavaBratislava2582005Slovakia Department of Information Systems and Networks Lviv Polytechnic National UniversityLviv79013Ukraine

To solve the problem of energy efficiency of modern enterprise it is necessary to reduce energy *** of the possible ways is proposed in this research.A multi-level hierarchical system for energy efficiency management of the enterprise is designed,it is based on the modular principle providing rapid *** novelty of the work is the development of new and improvement of the existing methods and models,in particular:1)models for dynamic analysis of IT tools for data acquisition and processing(DAAP)in multilevel energy management systems,which are based on Petri nets;2)method of synthesis of DAAP tools in energy efficiency management information systems(EEMIS)of the enterprise which provides a reduction in hardware and time costs from 10%to 40%;3)method of conflict-free data exchange determining the minimum memory speed for the synthesis of realtime exchanges,it reduces the cost and energy consumption;4)method of calculating the signal of postsynaptic excitation of neural elements decreases the processing time of technological data two or more *** proposed methods,models and tools have been tested while implementing the EEMIS of the intelligent mini-greenhouse,as a result,energy efficiency has increased by 12%-25%(depending on season and peculiarities of growing plants).

关键词： Energy efficiency management information system(EEMIS) data acquisition and processing(DAAP) industry 4.0 Petri nets smart mini greenhouse

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Parallel Driving with Big Models and Foundation Intelligence in Cyber-hysical-ocial Spaces

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Research 2024年第2期2024卷 1-17页

作者： Xiao Wang Jun Huang Yonglin Tian Chen Sun Lie Yang Shanhe Lou Chen Lv Changyin Sun Fei-Yue Wang School of Artificial Intelligence Anhui UniversityHefeiChina Macao University of Science and Technology MacaoChina State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina MVSLab Department of Mechanical and Mechatronics EngineeringUniversity of Waterloo200 University Ave WestWaterlooON N2L3G1Canada School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingaporeSingapore

Recent years have witnessed numerous technical breakthroughs in connected and autonomous vehicles (CAVs). On the one hand, these breakthroughs have significantly advanced the development of intelligent transportation systems (ITSs);on the other hand, these new traffic participants introduce more complex and uncertain elements to ITSs from the social space. Digital twins (DTs) provide real-time, data-driven, precise modeling for constructing the digital mapping of physical-world ITSs. Meanwhile, the metaverse integrates emerging technologies such as virtual reality/mixed reality, artificial intelligence, and DTs to model and explore how to realize improved sustainability, increased efficiency, and enhanced safety. More recently, as a leading effort toward general artificial intelligence, the concept of foundation model was proposed and has achieved significant success, showing great potential to lay the cornerstone for diverse artificial intelligence applications across different domains. In this article, we explore the big models embodied foundation intelligence for parallel driving in cyber-physical-social spaces, which integrate metaverse and DTs to construct a parallel training space for CAVs, and present a comprehensive elucidation of the crucial characteristics and operational mechanisms. Beyond providing the infrastructure and foundation intelligence of big models for parallel driving, this article also discusses future trends and potential research directions, and the ?S?goals of parallel driving.

关键词： breakthrough integrate corners

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Consistent Counterfactual Explanations via Anomaly control and Data Coherence

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第4期6卷 794-804页

作者： Movin, Maria Siciliano, Federico Ferreira, Rui Silvestri, Fabrizio Tolomei, Gabriele Spotify StockholmSE-111 Sweden Sapienza University of Rome Department of Computer Control and Management Engineering Rome00185 Italy Spotify LondonWC2N 6AT United Kingdom Sapienza University of Rome Department of Computer Science Rome00161 Italy

Algorithmic recourses are popular methods to provide individuals impacted by machine learning models with recommendations on feasible actions for a more favorable prediction. Most of the previous algorithmic recourse methods work under the assumption that the predictive model does not change over time. However, in reality, models in deployment may both be periodically retrained and have their architecture changed. Therefore, it is desirable that the recourse should remain valid when such a model update occurs, unless new evidence arises. We call this feature consistency. This article presents anomaly control and data coherence (ACDC), a novel model-agnostic recourse method that generates counterfactual explanations, i.e., instance-level recourses. ACDC is inspired by anomaly detection methods and uses a one-class classifier to aid the search for valid, consistent, and feasible counterfactual explanations. The one-class classifier asserts that the generated counterfactual explanations lie on the data manifold and are not outliers of the target class. We compare ACDC against several state-of-the-art recourse methods across four datasets. Our experiments show that ACDC outperforms baselines both in generating consistent counterfactual explanations, and in generating feasible and plausible counterfactual explanations, while still having proximity measures similar to the baseline methods targeting the data manifold. © 2024 IEEE.

关键词： Machine learning

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SELECTION PROBLEMS OF CURRENT TRANSFORMERS CHARACTERISTICS AT THE DESIGN STAGE WITH REQUIREMENTS FOR CORRECT OPERATION UNDER TRANSIENT MODES 6

SELECTION PROBLEMS OF CURRENT TRANSFORMERS CHARACTERISTICS A...

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6th International Scientific and Technical Conference Relay Protection and Automation, RPA 2023

作者： Yablokov, A.A. Panashchatenko, A.V. Titov, V.A. Maltsev, R.A. Electric power systems automatic control department Electric systems department Ivanovo State Power Engineering University named after V.I. Lenin Ivanovo Russia

ISBN: (纸本)9798350382334

Modern normative technical documentation in the field of design and operation of power facilities [1] imposes new requirements on current transformers (CTs) operation. The technical characteristics of CTs and the connected relay protection devices as a whole must ensure the correct operation of the devices during short-circuits (SCs), including when an aperiodic current component occurs. This circumstance primarily applies to newly constructed and reconstructed power facilities. The process of creating design documentation for them must be carried out taking into account the new requirements, for which GOST R 58669-2019 [2] was developed and approved. According to it, in addition to the existing tests of selected CTs, it is necessary to perform calculations of the time to saturation of the magnetic core of each CT winding, high-speed relay protection devices are connected to which. The obtained time is compared with the minimum time required for the correct operation of the connected relay protection devices. Difficulties often occur in coordinating the characteristics of CTs selected at the design stage and the results of calculating the time to saturation of CT magnetic cores at the detailed design stage. Negative test results lead to the need to adjust the design characteristics of CTs and to additional labor costs for their approval. One of the solutions to the problem encountered in design practice is intentionally inflating the characteristics of CTs at the design stage in order to successfully pass the time to saturation test at the detailed design stage. It leads to unjustified financial costs and non-optimal selection of CTs. Therefore, it is relevant to develop methods for calculating CT characteristics taking into account the new requirements. © 2023 IEEE.

关键词： Electric instrument transformers

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Deep Learning-based Moving Object Segmentation:Recent Progress and Research Prospects

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Machine Intelligence Research 2023年第3期20卷 335-369页

作者： Rui Jiang Ruixiang Zhu Hu Su Yinlin Li Yuan Xie Wei Zou College of Information Engineering Shanghai Maritime UniversityShanghai201306China School of Computer Science and Technology East China Normal UniversityShanghai200062China Research Center of Precision Sensing and Control Institute of AutomationChinese Academy of SciencesBeijing100190China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing100190China

Moving object segmentation(MOS),aiming at segmenting moving objects from video frames,is an important and challenging task in computer vision and with various *** the development of deep learning(DL),MOS has also entered the era of deep models toward spatiotemporal feature *** paper aims to provide the latest review of recent DL-based MOS methods proposed during the past three ***,we present a more up-to-date categorization based on model characteristics,then compare and discuss each category from feature learning(FL),and model training and evaluation *** FL,the methods reviewed are divided into three types:spatial FL,temporal FL,and spatiotemporal FL,then analyzed from input and model architectures aspects,three input types,and four typical preprocessing subnetworks are *** terms of training,we discuss ideas for enhancing model *** terms of evaluation,based on a previous categorization of scene dependent evaluation and scene independent evaluation,and combined with whether used videos are recorded with static or moving cameras,we further provide four subdivided evaluation setups and analyze that of reviewed *** also show performance comparisons of some reviewed MOS methods and analyze the advantages and disadvantages of reviewed MOS methods in terms of ***,based on the above comparisons and discussions,we present research prospects and future directions.

关键词： Moving object segmentation(MOS) change detection background subtraction deep learning(DL) video understanding

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LI-DPS: A Long Sequence Dual Prediction Scheme Based on Informer for Efficient High-Frequency Data Transmission 50

LI-DPS: A Long Sequence Dual Prediction Scheme Based on Info...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Wu, Yu Yang, Bo Zhu, Dafeng Chen, Cailian Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China China Shanghai Engineering Research Center of Industrial Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9781665464543

High-frequency time-series data such as vibration signals will consume a lot of communication resources and require very high network bandwidth. Reducing the amount of data transmission while ensuring its availability is particularly important and challenging in high-frequency scenarios. Dual prediction scheme (DPS) can significantly reduce the amount of data transmission while ensuring data accuracy. However, traditional DPS cannot be applied to high-frequency scenarios due to the limitation of the mechanism design and model inference speed. We propose a novel long sequence DPS to efficiently reduce the volume of high-frequency data transmission in real time. To overcome the accuracy degradation due to gradient vanishing in long sequence prediction, we also propose an attention-based prediction model. Furthermore, we propose Informer to reduce the model’s computational complexity and enable fast inference and deployment on resource-constrained edge gateways. Experiments based on the real-world dataset show that the proposed scheme can efficiently cope with high-frequency data, reduce its transmission volume, and ensure data accuracy. © 2024 IEEE.

关键词： Prediction models

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Analysing and Modelling Human Trust to a Navigation Robot 2

Analysing and Modelling Human Trust to a Navigation Robot

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2nd Edition IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural engineering, MetroXRAINE 2023

作者： Onyeoru, Happy Chidi Wirth, Christopher Giles, Joshua Arvaneh, Mahnaz University of Sheffield Department of Automatic Control and Systems Engineering United Kingdom School of Medical Sciences University of Manchester United Kingdom

ISBN: (纸本)9798350300802

Human trust plays a crucial role in Human-Machine Interactions (HMIs) within autonomous systems. This paper delves into the factors that influence human trust in machines, including varying error rates and types made by the machine, as well as the human's ability to intervene and rectify errors. To explore these factors, we conducted three scenarios involving a simulated claw robot navigating through multiple objects to detect and locate a target object. The first scenario examined the effect of changing error rates on human trust in the machine. In the second scenario, we investigated how variability in speed and accuracy of reaching the target impacted human trust. Lastly, we explored whether human trust in the machine changed when individuals had the capability to intervene and correct severe errors made by the machine. We then proposed a regression model to estimate human trust. Our results showed that human trust is significantly affected by changes in error rates. Our participants reported a higher trust on robot with low speed but higher accuracy in performing the task than the robot with high speed but lower accuracy. Interestingly, the ability to intervene and correct the robot's errors improved the participants' trust in the robot. Our regression result showed that we can estimate trust using different type of errors committed by machine which can be applied in real world scenarios. © 2023 IEEE.

关键词： computational modelling error rates human-machine interactions (HMIs) machine or robot action perceptions target identification trust

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Hybrid control of a Variable-Speed Peristaltic PUMP

Hybrid Control of a Variable-Speed Peristaltic PUMP

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2024 American control Conference, ACC 2024

作者： Beijen, Michiel Op Smeijers, Thijs Tijman Boerrigter, Gijs Van Den Eijnden, Sebastiaan University of Twente Group of Precision Engineering Department of Engineering Technology Enschede7500 AE Netherlands Demcon High-Tech Systems Enschede7521 PH Netherlands Eindhoven University of Technology Control Systems Technology Group Department of Mechanical Engineering Eindhoven5600 MB Netherlands

ISBN: (纸本)9798350382655

Peristaltic pumps are used for transporting liquids within disposable tubes, and are commonly found in medical devices. The peristaltic pump principle, however, introduces disturbances, thereby distorting the desired rotational speed of the pump. Proportional plus double integral (PI2) control is commonly used to reject these disturbances, but at the cost of deteriorated transient response and robustness margins. To balance these trade-offs in a more desirable manner, in this paper we propose a hybrid PI2 control strategy that allows for reducing the steady-state error while maintaining robustness margins similar to linear PI2 control. Experiments on a representative setup demonstrate up to 45% improvement in disturbance rejection capabilities. © 2024 AACC.

关键词： Disturbance rejection

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