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2023 ieee conference on control technology and applications, ccta 2023

ISBN: (纸本)9798350335446

The proceedings contain 172 papers. The topics discussed include: cooperative hoisting with two crawler cranes under rope-velocity constraints;reference governor for constrained data-driven control of aerospace systems with unknown input-output dynamics;lifelong learning control of nonlinear systems with constraints using multilayer neural networks with application to mobile robot tracking;an approach to robust co-design of plant and closed-loop controller;an investigation of heuristic control strategies for multi-electrolyzer wind-hydrogen systems considering degradation;tuning of discrete-time angular droop controllers;path following or tracking model predictive control for towing kites – a question of formulation or learning?;singular dispersal solutions for a multi-agent differential game with angle-based cost function;and control of multiagent networks in the presence of misbehaving nodes without the knowledge of global network objective.

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The Sixth ieee conference on control technology and applications

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ieee control SYSTEMS MAGAZINE 2023年第2期43卷 103-109页

作者： Beghi, Alessandro Dabbene, Fabrizio

Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.

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The Sixth ieee conference on control technology and applications [conference Reports]

The Sixth IEEE Conference on Control Technology and Applicat...

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作者： Beghi, Alessandro Dabbene, Fabrizio

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The Seventh ieee conference on control technology and applications

The Seventh IEEE Conference on Control Technology and Applic...

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作者： Alleyne, Andrew Barton, Kira

The control cationsSeventh(ieee technology ieeecctaconference and 2023) Appli- tookon place from 16 to 18 August at the Hilton Barbados in Bridgetown, Barbados. Technical workshops were held on Tuesday, 15 August. ...

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Research on UAV Data Anomaly Detection and Early Trajectory Warning technology 5

Research on UAV Data Anomaly Detection and Early Trajectory ...

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5th ieee International conference on Power, Electronics and Computer applications, ICPECA 2025

作者： Qian, Yucheng Zhao, Changwei Huang, Weiming Wang, Shudong Institute of Electric Power Science State Grid Anhui Electric Power Co. Ltd Hefei China State Grid Anhui Electric Power Co. Ltd Equipment Management Department Hefei China

ISBN: (纸本)9798331533694

In complex substation environments, the flight safety problem when unmanned aerial vehicles perform inspection tasks becomes more and more prominent. Currently, the flight control system is the main means of UAV flight status monitoring, but it lacks in-depth analysis of flight data, especially flight trajectory data. To make full use of the flight control system data, this paper proposes an anomaly detection and trajectory prediction method. Firstly, the local temporal features of the original data in the subspace are extracted, and the anomaly detection of the flight data is achieved by measuring the changes of the data subspace vectors on the basis of reducing the computational complexity of the data, followed by dynamically adjusting the thresholds of the anomalous data by using one-class support vector machines. And finally, the UAV trajectory prediction is performed by using a time-series based LSTM neural network, focusing on the anomalies that may affect the safety of flights Data Early Warning. © 2025 ieee.

关键词： Support vector machines

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Remote State Estimation and Blum–Shub–Smale Machines—A Computability Analysis With applications to Virtual Twinning

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ieee Transactions on Automatic control 2025年第5期70卷 3165-3180页

作者： Boche, Holger Bock, Yannik Deppe, Christian Fitzek, Frank H. P. Technical University of Munich Chair of Theoretical Information Technology MunichD-80290 Germany BMBF Research Hub 6G-Life D-80333 Munich Germany MunichD-80799 Germany MunichD-80807 Germany Technische Universität Braunschweig Institute for Communications Technology BraunschweigD-38106 Germany 5G Lab Germany DresdenD-01062 Germany

This article analyzes aspects of the problem of remote state estimation (RSE) via noisy communication channels for their Blum–Shub–Smale (BSS) computability, motivated by an exemplary application to a formal model of virtual twinning subject to stringent integrity requirements. Computability theory provides a unique framework for the formal and mathematically rigorous analysis of algorithms and computing machines. Therefore, computability theory is essential in the domain of safety- and life-critical technology, where the formal verification of automated systems is necessary. Based on the RSE problem, we establish a simple mathematical model of virtual-twin systems that entails a formal notion of integrity (i.e., a state where the virtual entity accurately mirrors its physical counterpart). The model's notion of integrity is related to the question of whether the system under consideration is capable of computing the communication channel's zero-error capacity and corresponding zero-error codes. While this task is known to exceed the theoretical capabilities of Turing computers, we prove its formal feasibility within the model BSS machines. As different authors have proposed BSS machines as potential model of some forms of analog computing, this article serves as a proof-of-concept for a theoretical analog supremacy of unconventional information-processing hardware. Considering recent advances in the development of such hardware, forms of analog supremacy will likely become relevant in the future of cyber-physical systems and information technology. © 1963-2012 ieee.

关键词： Computability and decidability

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ASTGNN: Adaptive Spatio-Temporal Graph Neural Network for Motor Imagery Recognition

ASTGNN: Adaptive Spatio-Temporal Graph Neural Network for Mo...

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2024 International conference on Mechatronics and Intelligent control, ICMIC 2024

作者： Zhao, Zheng Xue, Haixiao Huang, Yuwen Zhao, Qi Xie, Xin Dalian Maritime University Dalian China Northeastern University Shenyang China Hunan University of Information Technology Changsha China Hunan Province Higher Education Key Laboratory of Intelligent Sensing and Computing Changsha China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

Motor imagery electroencephalogram recognition is a key area in brain-computer interfaces, with applications in human-computer interaction, rehabilitation, and virtual reality. Traditional methods often overlook the brain's topological characteristics and the correlations between EEG channels, resulting in suboptimal decoding. To address this, we propose an adaptive spatio-temporal graph neural network (ASTGNN), which constructs a brain graph topology and adaptively learns the topological adjacency matrix, exploring both common and individual electrode connections. The spatial features are extracted using a graph convolutional network, while a gated position-aware self-attention mechanism captures movement information and global dependencies, enhancing temporal feature extraction. Experiments show that ASTGNN significantly improves recognition, achieving an average accuracy of 87.36%. © 2025 SPIE.

关键词： Electroencephalography

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Integrating the dynamic optimization strategies of Adam and AdaGrad 13

Integrating the dynamic optimization strategies of Adam and ...

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13th International conference on Intelligent control and Information Processing, ICICIP 2025

作者： Huang, Zhixuan Luo, Xiaonan Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin China

ISBN: (纸本)9798331516147

Artificial intelligence (AI) has been a key research area since the 1950s, initially focused on using logic and reasoning to create systems that understand language, control robots, and offer expert advice. With the rise of big data and deep learning, AI has advanced in applications like recommendation systems, image recognition, and machine translation, primarily through optimizing loss functions in deep neural networks to improve accuracy and reduce training *** descent is the core optimization method but faces challenges like slow convergence and local minima. To overcome these, algorithms like Momentum, AdaGrad, RMSProp, Adadelta, Adam, and Nadam have been developed, introducing momentum and adaptive learning rates to accelerate convergence. This paper presents a new optimization algorithm that combines the strengths of Adam and AdaGrad, offering better adaptability to different learning rates. © 2025 ieee.

关键词： Contrastive Learning

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Fabrication of Wafer-Bonded 2D CMUT Array with Glass-Filled Trenches 38

Fabrication of Wafer-Bonded 2D CMUT Array with Glass-Filled ...

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38th ieee International conference on Micro Electro Mechanical Systems, MEMS 2025

作者： Oh, Chaerin Park, Seyoung Park, Jongcheol Jung, Joontaek Lee, Hyunjoo J. Korea Advanced Institute of Science and Technology School of Electrical Engineering Korea Republic of National NanoFab Center Center for Next-Generation Platform Development Korea Republic of

ISBN: (纸本)9798331508890

Precise modulation of the focused beam is a critical technology for improving the performance of ultrasound-based treatments and diagnostics. Beyond conventional 1D transducer arrays, 2D transducer arrays have significantly broadened the scope of beam control applications. Leveraging CMOS compatibility, capacitive micromachined ultrasonic transducers (CMUT) have been regarded as an effective approach to fabricating 2D transducer arrays in a compact form. Although wafer-bonded CMUT arrays demonstrate excellent performance, their complex structures, including through-substrate vias and the need for mechanical stability, have posed significant challenges for 2D arrays. To address these challenges, we propose a novel method to enhance mechanical stability by employing a glass-reflow technique to fill the trench. © 2025 ieee.

关键词： Wafer bonding

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Location Data Publishing Mechanism in Semi-Trusted Vehicle Networks based on Differential Privacy

Location Data Publishing Mechanism in Semi-Trusted Vehicle N...

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2024 International conference on Mechatronics and Intelligent control, ICMIC 2024

作者： Zhao, Zheng Zhang, Tianhao Mao, Qian Zhao, Qi Xie, Xin Dalian Maritime University Dalian China Liaoning University Shenyang China Northeastern University Shenyang China Hunan University of Information Technology Changsha China Hunan Province Higher Education Key Laboratory of Intelligent Sensing and Computing Changsha China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

Vehicular ad-hoc networks (VANETs) are essential in mobile ad-hoc network applications, utilizing vehicle location data. However, safeguarding the privacy and security of this data is challenging, especially with untrusted roadside units. To address this, we propose a novel differential privacy-based location data publishing mechanism. It consists of three key components: dynamic group leader selection, data aggregation, and privacy-preserving data publishing. The group leader selection algorithm is based on directional thresholds, hop cycles, and lifespans, assuming semi-trusted vehicles. Additionally, the differential privacy-based algorithm uses map grid segmentation, privacy budget recovery, and a filtering mechanism to ensure location privacy. Comparative experiments show that our scheme outperforms existing models in total hops, group leader lifetime, and mean absolute error. © 2025 SPIE.

关键词： Differential privacy

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