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IEEE Conference on Decision and control

作者： Benedikt Andritsch Lars Watermann Stefan Koch Markus Reichhartinger Johann Reger Martin Horn Institute of Automation and Control at Graz University of Technology Graz Austria Control Engineering Group Technische Universität Ilmenau Ilmenau Germany

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this paper an implementation of sliding mode control for disturbed integrator chains that does not suffer from the discretization chattering effect is presented. The method is based on an Euler forward discretization of the sliding mode controller. In a vicinity of the origin, that properly scales with the discretization time, the controller is altered to eliminate discretization chattering which can also improve the control accuracy. Finite-time stability of the origin is proven in the absence of a disturbance. In the disturbed case boundedness of the control error is shown. The control actuation is shown to be locally bounded. Exemplary applications to first- and second-order sliding mode control show the effectiveness of the method.

关键词： Accuracy Sliding mode control

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Haptic-Aided Navigation Vehicle: Enhancing Obstacle Detection in Blind Spots and Transparent Object Scenarios

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Journal of Shanghai Jiaotong University (Science) 2025年 1-9页

作者： Li, Mingwang Li, Xinde Zhang, Zhentong Zhang, Zeyu Zhao, Haoming School of Software Southeast University Suzhou Jiangsu215000 China School of Automation Southeast University Nanjing210018 China School of Cyber Science and Engineering Southeast University Nanjing211102 China Key Laboratory of Measurement and Control of Complex Systems of Engineering of Ministry of Education Nanjing214135 China Nanjing Center for Applied Mathematics Nanjing211135 China Southeast University Shenzhen Research Institute Shenzhen Guangdong518063 China

As autonomous mobile robots are increasingly deployed in complex environments, traditional vision sensors and LiDAR encounter considerable limitations, particularly in detecting obstacles in blind spots or transparent objects. To address the issue of blind spots, we design a specialized haptic sensing structure and develop the haptic-aided navigation vehicle (HANV). This system integrates haptic sensors and LiDAR to deliver comprehensive perception, significantly enhancing close-range obstacle detection in areas that are typically beyond the range of conventional sensors. To tackle the challenge of transparent obstacles, which are often undetected by both vision and LiDAR sensors, we employ a fusion of haptic sensors and LiDAR. The haptic system provides physical contact feedback, ensuring reliable detection of transparent obstacles such as glass, while LiDAR offers long-range sensing capabilities. This combination enables HANV to navigate effectively in environments with transparent obstacles, overcoming the limitations of traditional sensing systems. Experiment results indicate that the proposed haptic and LiDAR integration substantially improves obstacle detection in both blind spots and environments with transparent obstacles. HANV achieves high success rates, minimal collisions, and efficient obstacle avoidance, particularly excelling in complex, confined spaces where conventional systems prove inadequate. These findings emphasize the efficacy of our approach in enhancing navigation performance in dynamic and challenging environments. (Figure presented.) © Shanghai Jiao Tong University 2025.

关键词： Mobile robots

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TBANet: Three Branches with Asymmetric Convolutions and Pooling for Real-time Semantic Segmentation

TBANet: Three Branches with Asymmetric Convolutions and Pool...

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2022 International Conference on Intelligent Manufacturing and Industrial Big Data, ICIMIBD 2022

作者： Qin, Hao Chen, Zhenxue Lu, Mengxu Cao, Jiaqian Zhao, Hongjian Shandong University School of Control Science and Engineering Jinan China Machinery Industry CO Beijing Research Institute of Automation Beijing China

ISBN: (纸本)9798350320305

Computational pressure limits the application of semantic segmentation in road scenes. We propose the lightweight network TBANet that makes a trade-off between accuracy and speed to deal with this problem. TBANet takes advantage of three branches (a fine-grained branch, an adaptive branch, and a coarse-grained branch) to obtain detailed and abstract information and adaptively supplement useful features for semantic segmentation. In order to exploit the information in the horizontal and vertical directions in images and remove redundant information to speed up, we propose the Asymmetric Pyramid Pooling Module (APPM) and the Asymmetric Factorized Module (AFM). TBANet with only 1M parameters processes 512×1024 images at 143 FPS and achieves 71.6% mIoU on the Cityscapes test set. TBANet stands out from other state-of-the-art networks in terms of accuracy and speed. © 2022 IEEE.

关键词： Semantic Segmentation

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The Caching and Pricing Strategy for Information-Centric Networking with Advertisers’Participation

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China Communications 2024年第3期21卷 283-295页

作者： Zheng Quan Yan Wenliang Wu Rong Tan Xiaobin Yang Jian Yuan Liu Xu Zhenghuan Laboratory for Future Networks Department of AutomationUniversity of Science and Technology of ChinaHefei 230026China Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei 230088China Institute of Advanced Technology University of Science and Technology of ChinaHefei 230088China Suzhou Nuclear Power Research Institute Suzhou 215004China National Engineering Laboratory for Public Safety Risk Perception and Control by Big Data(NEL-PSRPC) China Academy of Electronics and Information Technology of CETCBeijing 100041China

As users’access to the network has evolved into the acquisition of mass contents instead of IP addresses,the IP network architecture based on end-to-end communication cannot meet users’***,the Information-Centric Networking(ICN)came into *** a technical point of view,ICN is a promising future network *** and customizing a reasonable pricing mechanism plays a positive role in promoting the deployment of *** current research on ICN pricing mechanism is focused on paid ***,we study an ICN pricing model for free content,which uses game theory based on Nash equilibrium to *** this work,advertisers are considered,and an advertiser model is established to describe the economic interaction between advertisers and ICN *** solution can formulate the best pricing strategy for all ICN entities and maximize the benefits of each *** extensive analysis and numerical results show that the proposed pricing framework is significantly better than existing solutions when it comes to free content.

关键词： advertisers cache free content Information-Centric Networking pricing strategy

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BFuse-Net: Bonferroni Mean Operator-Aided Fusion of Neural Networks for Medical Image Classification 5th

BFuse-Net: Bonferroni Mean Operator-Aided Fusion of Neural ...

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5th International Conference on Medical Imaging and Computer Aided Diagnosis, MICAD 2024

作者： Ghosh, Triyas Chakraborty, Soham Kaplun, Dmitrii Gulvanskii, Vyacheslav Sarkar, Ram Department of Computer Science and Engineering Jadavpur University Kolkata700032 India Artificial Intelligence Research Institute China University of Mining and Technology Xuzhou China Department of Automation and Control Processes Saint Petersburg Electrotechnical University "LETI" Saint Petersburg Russia

ISBN: (纸本)9789819638628

In this paper, we have proposed a novel model, called Bonferroni Mean Operator-aided Fusion of Neural Networks (BFuse-Net). Here, we have taken advantage of the capabilities of four deep learning models as the base learners and then applied a customized attention method to prioritize different fine-grained features by passing their outputs via four parallel pipelines. Next, we have employed a novel aggregation method, a modified Bonferroni Mean operator, to merge the decision scores acquired from every pipeline, prioritizing their individual contributions above their interactions with others in the decision scores. Three medical image datasets— LC25000 (colon cancer), Oral Squamous Cell Carcinoma, and Malaria Cell Images have been used for experimentation. The model yields state-of-the-art outcomes for the three datasets. The source codes and additional results can be found at GitHub repository. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep learning

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Safety Metric Aware Trajectory Repairing for Automated Driving 27

Safety Metric Aware Trajectory Repairing for Automated Drivi...

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27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024

作者： Tong, Kailin Dikic, Berin Xiao, Wenbo Steinberger, Martin Horn, Martin Solmaz, Selim Virtual Vehicle Research GmbH Inffeldgasse 21a Graz8010 Austria Institute of Automotive Engineering Graz University of Technology Inffeldgasse 11 Graz8010 Austria Institute of Automation and Control Graz University of Technology Inffeldgasse 21b Graz8010 Austria

ISBN: (纸本)9798331505929

Recent analyses highlight challenges in autonomous vehicle technologies, particularly failures in decision-making under dynamic or emergency conditions. Traditional automated driving systems recalculate the entire trajectory in a changing environment. Instead, a novel approach retains valid trajectory segments, minimizing the need for complete replanning and reducing changes to the original plan. This work introduces a trajectory repairing framework that calculates a feasible evasive trajectory while computing the Feasible Time-to-React (F-TTR), balancing the maintenance of the original plan with safety assurance. The framework employs a binary search algorithm to iteratively create repaired trajectories, guaranteeing both the safety and feasibility of the trajectory repairing result. In contrast to earlier approaches that separated the calculation of safety metrics from trajectory repairing, which resulted in unsuccessful plans for evasive maneuvers, our work has the anytime capability to provide both a Feasible Time-to-React and an evasive trajectory for further execution. © 2024 IEEE.

关键词： Trajectories

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Prediction of Remaining Useful Life Based on SSA-RVM-PF Method for Lithium-ion Battery 5

Prediction of Remaining Useful Life Based on SSA-RVM-PF Meth...

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5th International Symposium on Autonomous Systems, ISAS 2022

作者： Zhou, Meng Wang, Jing Cai, Chang Wang, Chang North China University of Technology School of Electrical and Control Engineering Beijing China Beijing Aerospace Automation Research Institute Beijing China

ISBN: (纸本)9781665487085

To improve the prediction accuracy of the remaining useful life of lithium-ion battery, a novel SSA-RVM-PF prediction method is proposed. The key prediction mechanism of the proposed method is based on the relevance vector machine (RVM) method. Based on the strong regression ability of RVM, the optimal degradation trajectory of battery capacity can be predicted. Meanwhile, a sparrow search algorithm (SSA) is used to optimize the kernel function parameters of RVM method. Furthermore, a particle filtering (PF) strategy is constructed based on the degradation trajectory, in which the state space model. Simulation results show that the proposed prediction method has the characteristics of high fitting degree of state tracking and high prediction accuracy. © 2022 IEEE.

关键词： Lithium-ion batteries

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Analysis of coupled axial-torsional vibration of drill-string with an inclination angle 41

Analysis of coupled axial-torsional vibration of drill-strin...

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第41届中国控制会议

作者： Jiahao Zhang Chengda Lu Hengyu Huang Jun Gao Min Wu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education CCTEG Xi'an Research Institute

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Drill-string vibration has a great negative influence on the safety and efficiency of geological *** that the influence of drill-string inclination is not well considered in the literature,this paper develops a novel drill-string vibration model for geological drilling with inclined ***,the correlation between the inclination angle of borehole and the axial and torsional forces on the drill-string is *** on this,a drill-string motion model with the parameters of inclination angle is ***,the bit-rock interaction is considered as two processes,axial cutting and torsional friction,and an axial-torsional coupled bit-rock interaction model with state-dependent time delay is *** combining the established drill-string motion model and bit-rock interaction model,a coupled axial-torsional vibration model of drill-string in inclined borehole is obtained with the effect of borehole wall friction taken into *** drill-string vibration model proposed in this paper is more general,and includes the existing coupled drill-string vibration model of vertical borehole,which is closer to the actual situation.

关键词： drill-string vibration drill-string inclination bit-rock interaction

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EFEAR-4D: Ego-Velocity Filtering for Efficient and Accurate 4D radar Odometry

arXiv

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arXiv 2024年

作者： Wu, Xiaoyi Chen, Yushuai Li, Zhan Hong, Ziyang Hu, Liang The Department of Automation School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin150001 China

Odometry is a crucial component for successfully implementing autonomous navigation, relying on sensors such as cameras, LiDARs and IMUs. However, these sensors may encounter challenges in extreme weather conditions, such as snowfall and fog. The emergence of FMCW radar technology offers the potential for robust perception in adverse conditions. As the latest generation of FWCW radars, the 4D mmWave radar provides point cloud with range, azimuth, elevation, and Doppler velocity information, despite inherent sparsity and noises in the point cloud. In this paper, we propose EFEAR-4D, an accurate, highly efficient, and learning-free method for large-scale 4D radar odometry estimation. EFEAR-4D exploits Doppler velocity information delicately for robust ego-velocity estimation, resulting in a highly accurate prior guess. EFEAR-4D maintains robustness against point-cloud sparsity and noises across diverse environments through dynamic object removal and effective region-wise feature extraction. Extensive experiments on two publicly available 4D radar datasets demonstrate state-of-the-art reliability and localization accuracy of EFEAR-4D under various conditions. Furthermore, we have collected a dataset following the same route but varying installation heights of the 4D radar, emphasizing the significant impact of radar height on point cloud quality - a crucial consideration for real-world deployments. Our algorithm and dataset will be available soon at https://***/CLASS-Lab/EFEAR-4D. © 2024, CC BY-NC-SA.

关键词： Millimeter waves

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Fuzzy cascade control of heating furnace outlet temperature based on improved particle swarm optimization 10

Fuzzy cascade control of heating furnace outlet temperature ...

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10th International Conference on Mechanical engineering, Materials, and automation Technology, MMEAT 2024

作者： Qi, Jiaxin Hu, Shaolin He, Hongli Zhang, Sai College of Electronic Information Engineering Xi’an Technological University Xi’an710000 China Automation School Guangdong University of Petrochemical Technology Guangdong Maoming525000 China Institute of China Academy of Flight Test and Research Xi'an Xi’an710000 China School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin132000 China

ISBN: (纸本)9781510682634

To address the nonlinearities and multiple disturbances encountered in the outlet temperature control system of the heating furnace, a fuzzy cascade control system is devised. This system integrates the strengths of both cascade control and fuzzy control, aiming to effectively regulate the outlet temperature of the heating furnace. To enhance the system's control effectiveness, an Improved Particle Swarm Optimization algorithm is introduced for optimizing the fuzzy PID cascade control method. The method optimizes the parameters of the outer loop controller (i.e., fuzzy PID controller) in the fuzzy cascade control system, by introducing a nonlinear decreasing function to enhance the weights, utilizing Tent mapping to improve the random number r, and employing a logarithmic function to construct a nonlinear asynchronous learning factor. The simulation results indicate that when compared to three other control methods—conventional cascade PID, fuzzy cascade PID, and particle swarm-optimized fuzzy cascade PID—the proposed control method in this paper exhibits reduced overshoot by 16.9%, 10.5%, and 3.1%, respectively. Additionally, the regulation time is shortened by 36s, 16s, and 12s, respectively. thereby significantly enhancing the system's control performance. © 2024 SPIE.

关键词： Particle swarm optimization (PSO)

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