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第43届中国控制会议

作者： Nanyan Li Hao Chen Zhigang Sun Jing Gao Dewei Yi Cunjia Liu Jinya Su School of Automation Southeast University Key Laboratory of Measurement and Control of CSE Ministry of Education Southeast University State Grid Jiangsu Integrated Energy Service Co. Ltd. Department of Computing Science University of Aberdeen Department of Aeronautical and Automotive Engineering Loughborough University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

This paper considers the real-time semantic segmentation of solar PhotoVoltaic(PV) arrays using down-facing cameras onboard Unmanned Aerial Vehicles(UAVs) to support autonomous navigation for ultra-low altitude industrial inspection. Various semantic segmentation algorithms, including SegNet, UNet, Deeplabv3+, and their respective variants, are compared to identify the most suitable one that strikes a balance between segmentation and real-time performance. Subsequently, each video frame is processed by the selected segmentation network to create a solar array mask. This mask is then optimally fitted to diverse solar array shapes to determine angular and horizontal deviations between the image center and the solar array center-line. The algorithms are validated on a self-constructed dataset of 594 solar PV array UAV images, encompassing varied environmental conditions and solar farm layouts. The top-performing network, lightweight vgg16bn-Unet, achieves 99.4% overall accuracy and 98.2% Intersection over Union(IoU), while the most balanced network, mobilev3-Deeplabv3+, attains 98.9% accuracy and96.5% IoU, with a 27.59 fps(using an NVIDIA GeForce MX150 GPU) suitable for real-time UAV flights.

关键词： CNN Machine Vision Solar Inspection UAV Navigation Real-time and Embedded systems

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Parks-McClellan Algorithm-Based Active Damping Strategy Applied to Grid-Connected Inverters

Parks-McClellan Algorithm-Based Active Damping Strategy Appl...

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IEEE Annual Southern Power Electronics Conference (SPEC)

作者： José de Arimatéia O. Filho Gabriel Lucas Bressanini Tiago Davi Curi Busarello Luis De Oro Arenas Paulo Fernando Silva Helmo Kelis Morales Paredes Group of Automation and Integratd Systems (GASI) São Paulo State University (Unesp) Sorocaba Brazil Department of Control Automation and Computing Engineering Federal University of Santa Catarina (UFSC) Blumenau Brazil

In recent years, grid-connected inverters have gained wide prominence, primarily attributed to the surge in distributed energy resources. To ensure the reliable operation of these inverters, it is crucial to adequately damp the resonance peak of the LCL filter at the inverter output. By achieving this, the grid-connected inverter guarantees the system's stability while minimizing the harmonic content in the current injected into the distribution grid. To address this issue, this paper proposes the utilization of digital differentiators in conjunction with optimized wideband differentiators, which are designed using the Parks-McClellan (PM) algorithm. These differentiators are applied specifically to the LCL filter capacitor voltage to dampen the resonance peak effectively. Simulation results univocally demonstrate the effectiveness of the proposed approach.

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Protecting Personalized Trajectory with Differential Privacy under Temporal Correlations

Protecting Personalized Trajectory with Differential Privacy...

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IEEE Conference on Wireless Communications and Networking

作者： Mingge Cao Haopeng Zhu Minghui Min Yulu Li Shiyin Li Hongliang Zhang Zhu Han School of Information and Control Engineering China University of Mining and Technology Xuzhou China Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of CyberScience and Engineering Wuhan University Wuhan China School of Electronics Peking University Beijing China Department of Electrical and Computer Engineering University of Houston Houston TX USA

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

Location-based services (LBSs) in vehicular ad hoc networks (VANETs) offer users numerous conveniences. However, the extensive use of LBSs raises concerns about the privacy of users' trajectories, as adversaries can exploit temporal correlations between different locations to extract personal information. Additionally, users have varying privacy requirements depending on the time and location. To address these issues, this paper proposes a personalized trajectory privacy protection mechanism (PTPPM). This mechanism first uses the temporal correlation between trajectory locations to determine the possible location set for each time instant. We identify a protection location set (PLS) for each location by employing the Hilbert curve-based minimum distance search algorithm. This approach incor-porates the complementary features of geo-indistinguishability and distortion privacy. We put forth a novel Permute-and-Flip mechanism for location perturbation, which maps its initial application in data publishing privacy protection to a location perturbation mechanism. This mechanism generates fake locations with smaller perturbation distances while improving the balance between privacy and quality of service (QoS). Simulation results show that our mechanism outperforms the benchmark by providing enhanced privacy protection while meeting user's QoS requirements.

关键词： Privacy Correlation Publishing Perturbation methods Simulation Vehicular ad hoc networks Quality of service

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A Trusted Lesion-assessment Network for Interpretable Diagnosis of Coronary Artery Disease in Coronary CT Angiography 39

A Trusted Lesion-assessment Network for Interpretable Diagno...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Ma, Xinghua Fang, Xinyan Zou, Mingye Luo, Gongning Wang, Wei Wang, Kuanquan Qiu, Zhaowen Gao, Xin Li, Shuo Faculty of Computing Harbin Institute of Technology Harbin China Computational Bioscience Research Center King Abdullah University of Science and Technology Thuwal Saudi Arabia Faculty of Computing Harbin Institute of Technology Shenzhen China College of Computer and Control Engineering Northeast Forestry University Harbin China Department of Computer and Data Science Case Western Reserve University Cleveland United States Department of Biomedical Engineering Case Western Reserve University Cleveland United States

ISBN: (纸本)157735897X

Coronary Artery Disease (CAD) poses a significant threat to cardiovascular patients worldwide, underscoring the critical importance of automated CAD diagnostic technologies in clinical practice. Previous technologies for lesion assessment in Coronary CT Angiography (CCTA) images have been insufficient in terms of interpretability, resulting in solutions that lack clinical reliability in both network architecture and prediction outcomes, even when diagnoses are accurate. To address the limitation of interpretability, we introduce the Trusted Lesion-Assessment Network (TLA-Net), which provides a clinically reliable solution for multi-view CAD diagnosis: (1) The causality-informed evidence collection constructs a causal graph for the diagnostic process and implements causal interventions, preventing confounders’ interference and enhancing the transparency of the network architecture. (2) The clinically-aligned uncertainty integration hierarchically combines Dirichlet distributions from various views based on clinical priors, offering confidence coefficients for prediction outcomes that align with physicians’ image analysis procedures. Experimental results on a dataset of 2,618 lesions demonstrate that TLA-Net, supported by its interpretable methodological design, exhibits superior performance with outstanding generalization, domain adaptability, and robustness. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

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Key technologies for electric vehicles

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Green Energy and Intelligent Transportation 2022年第2期1卷 135-137页

作者： Rui Xiong Jonghoon Kim Weixiang Shen Chen Lv Hailong Li Xiaoyong Zhu Wanzhong Zhao Bingzhao Gao Hongyan Guo Chengming Zhang Fengchun Sun Department of Vehicle Engineering School of Mechanical EngineeringBeijing Institute of TechnologyNo.5 South Zhongguancun StreetHaidian DistrictBeijing 100081China Energy Storage and Conversion Laboratory Department of Electrical EngineeringCollege of EngineeringChungnam National UniversityDaejeon34134South Korea School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyHawthornVictoria 3122Australia School of Mechanical and Aerospace Engineering Nanyang Technological University639798Singapore School of Business Society and Engineering Mälardalen UniversitySE 72123VäteråsSweden School of Electrical and Information Engineering Jiangsu UniversityZhenjiangChina Department of Vehicle Engineering Nanjing University of Aeronautics and AstronauticsNanjingChina Clean Energy Automotive Engineering Center Tongji UniversityShanghai 201804China State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130022China Department of Electrical Engineering Harbin Institute of TechnologyHarbinChina

*** Electric vehicles(EVs)are playing an increasingly important role in decarbonizing the transportation *** constitute a promising solution to a set of global challenges such as climate change and air *** are an integration of a wide spectrum of techniques,such as battery monitoring,battery safety and vehicle energy *** this regard,the EV development still faces significant challenges,which necessitate innovations in EV *** this,Green Energy and Intelligent Transportation(GEITS)organizes a special issue of“Key Technologies for Electric Vehicles”that attempts to advance knowledge in the area of EVs and provides a platform for researchers and engineers to share recent research results and discuss critical challenges in this field.A wide spectrum of topics are discussed,including but not limited to the following.

关键词： battery Key challenges

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Intelligent Networked control of Vasoactive Drug Infusion for Patients with Uncertain Sensitivity

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Computer Systems Science & engineering 2023年第10期47卷 721-739页

作者： Mohamed Esmail Karar Amged Sayed A.Mahmoud College of Computing and Information Technology(CCIT) Shaqra UniversityShaqra11961Saudi Arabia Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering(FEE)Menoufia UniversityMenouf32952Egypt Department of Electrical Energy Engineering College of Engineering&TechnologyArab Academy for Science Technology&Maritime TransportP.O.Box 12577Smart VillageSmart Village-B 2401Egypt

Abnormal high blood pressure or hypertension is still the leading risk factor for death and disability *** paper presents a new intelligent networked control of medical drug infusion system to regulate the mean arterial blood pressure for hypertensive patients with different health status *** infusion of vasoactive drugs to patients endures various issues,such as variation of sensitivity and noise,which require effective and powerful systems to ensure robustness and good *** developed intelligent networked system is composed of a hybrid control scheme of interval type-2 fuzzy(IT2F)logic and teaching-learning-based optimization(TLBO)*** networked IT2F control is capable of managing the uncertain sensitivity of the patient to anti-hypertensive drugs *** avoid the manual selection of control parameter values,the TLBO algorithm is mainly used to automatically find the best parameter values of the networked IT2F *** simulation results showed that the optimized networked IT2F achieved a good performance under external disturbances.A comparative study has also been conducted to emphasize the outperformance of the developed controller against traditional PID and type-1 fuzzy ***,the comparative evaluation demonstrated that the performance of the developed networked IT2F controller is superior to other control strategies in previous studies to handle unknown patients’sensitivity to infused vasoactive drugs in a noisy environment.

关键词： Intelligent medical systems telemedicine fuzzy control teaching learning-based optimization

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Complex Permeability Determination for EE Core Based on Flexible PCB Fixture and Magnetic Flux Path Length Analysis

Complex Permeability Determination for EE Core Based on Flex...

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China Power Supply Society Electromagnetic Compatibility Conference (CPEMC)

作者： Huamin Jie Zhenyu Zhao Yongqi Chang Changdong Wang Shiqi Jiang Richard Xian-Ke Gao Kye Yak See School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Department of Electrical and Computer Engineering National Univeristy of Singapore Singapore Singapore Department of Control Science and Engineering Harbin Institute of Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China A*STAR Institute of High Performance Computing Singapore Singapore

ISBN: (数字)9798331509552

ISBN: (纸本)9798331509569

The complex permeability of magnetic cores acts as a vital factor in electromagnetic interference (EMI) filtering choke design and optimization. Many efforts have been reported for toroid cores, but fewer target those with other shapes, such as EE, EI, UU, and UI cores. Owing to their commonly used in planar EMI filters, determining the complex permeability of them is of significance. Targeting EE cores, this paper presents a flexible printed circuit board (PCB)-based fixture adapter tailored designed for performing the measurement, while the corresponding core permeability can be calculated through magnetic flux path length analysis. The experiments validate the effectiveness and accuracy of the proposed methods, spanning a wide frequency range up to 120 MHz.

关键词： Magnetic flux Accuracy Flexible printed circuits Magnetic cores Fixtures Electromagnetic interference Permeability measurement Length measurement Permeability Inductors

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Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose Estimation

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2025年第7期47卷 5520-5537页

作者： Jian Liu Wei Sun Hui Yang Pengchao Deng Chongpei Liu Nicu Sebe Hossein Rahmani Ajmal Mian National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering School of Robotics and the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an China Department of Information Engineering and Computer Science University of Trento Trento Italy School of Computing and Communications Lancaster University Lancaster U.K. Department of Computer Science The University of Western Australia Crawley WA Australia

Nine-degrees-of-freedom (9-DoF) object pose and size estimation is crucial for enabling augmented reality and robotic manipulation. Category-level methods have received extensive research attention due to their potential for generalization to intra-class unknown objects. However, these methods require manual collection and labeling of large-scale real-world training data. To address this problem, we introduce a diffusion-based paradigm for domain-generalized category-level 9-DoF object pose estimation. Our motivation is to leverage the latent generalization ability of the diffusion model to address the domain generalization challenge in object pose estimation. This entails training the model exclusively on rendered synthetic data to achieve generalization to real-world scenes. We propose an effective diffusion model to redefine 9-DoF object pose estimation from a generative perspective. Our model does not require any 3D shape priors during training or inference. By employing the Denoising Diffusion Implicit Model, we demonstrate that the reverse diffusion process can be executed in as few as 3 steps, achieving near real-time performance. Finally, we design a robotic grasping system comprising both hardware and software components. Through comprehensive experiments on two benchmark datasets and the real-world robotic system, we show that our method achieves state-of-the-art domain generalization performance.

关键词： Shape Solid modeling Three-dimensional displays Pose estimation Training Robots Grasping Diffusion models Real-time systems Point cloud compression

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Neighbor Patches Merging Reduces Spatial Redundancy of Nature Images

SSRN

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SSRN 2023年

作者： Jiang, Kai Peng, Peng Lian, Youzao Shao, Weihui Xu, Weisheng Department of Control Science and Engineering College of Electronic and Information Engineering Tongji University No. 4800 Caoan Highway Shanghai201804 China Education Technology and Computing Center Tongji University No. 1239 Siping Road Shanghai200092 China

The introduction of the Transformer architecture in Computer Vision has unified the processing of image and text data. However, Transformer networks encounter the quadratic complexity of computation with respect to the sequence length. To mitigate this challenge, the Vision Transformer (ViT) dissects images into patches, embedding them into tokens for network input and thereby reducing the sequence length. This study leverages spatial redundancy in nature images and incorporates adaptive within images. The proposed solution introduces the Neighbor Patch Merging (NEPAM) method, which merges the image patches at the network’s inception. NEPAM effectively reduces sequence length and accelerates inference without necessitating alterations to the networks. Furthermore, we observe that merging patches leads to the loss of position embeddings and accuracy/ To address this, we propose Multi-Scale Relative Position Embeddings (MS-RPE) to model the position relationship between patches with adaptive sizes. Both the NEPAM method and MS-RPE can be seamlessly integrated into the network, enabling more flexible model deployment. Experiments demonstrate that applying NEPAM and MS-RPE to Deit-Small models results in a 2.26x speedup with an accuracy loss of 2.44%, without the necessaity of retraining for a fixed pruning rate. © 2023, The Authors. All rights reserved.

关键词： Embeddings

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A Nonlinear Observer for a Flexible Robot Arm and its Use in Fault and Collision Detection

A Nonlinear Observer for a Flexible Robot Arm and its Use in...

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IEEE Conference on Decision and control

作者： Claudio Gaz Andrea Cristofaro Pasquale Palumbo Alessandro De Luca Department of Mechanical Engineering Faculty of Science Engineering and Computing Kingston University London UK Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy Department of Biotechnology and Biosciences University of Milano Bicocca Milan Italy

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

A nonlinear observer is presented for the estimation of the joint velocities and of the deformation modes and their rates for a two-link flexible robot arm, using only motor encoders and a tip position sensor. The state observer can be used then for trajectory tracking control. By monitoring the mismatch between measured and estimated outputs, we can also detect the occurrence of permanent or intermittent system anomalies such as actuator faults or link collisions.

关键词： Jacobian matrices Actuators Trajectory tracking Observers Arms Robot sensing systems Manipulators

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