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检索条件"任意字段=3rd International Conference on Robotics and Control Engineering, RobCE 2023"

共 3888 条记录，以下是51-60 订阅

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High-Speed Train Fault-Tolerant control Base on Fast Non-singular Terminal Sliding Mode control with NDOB and RFBNN 3rd

High-Speed Train Fault-Tolerant Control Base on Fast Non-sin...

引用

3rd international conference on Information control, Electrical engineering, and Rail Transit, ICEERT 2023

作者： Hao, Zixu Liu, Yumei Hu, Ting Liu, Pengcheng Liu, Jingzhuo Jilin University Changchun130022 China

ISBN: (纸本)9789819788903

Automatic control of high-speed trains, especially fault-tolerant control tracking, has become a research hotspot in recent years. This paper proposes an adaptive fault-tolerant controller based on fast non-singular terminal sliding mode control for the longitudinal dynamics model of the high-speed train. The controller utilizes nonlinear disturbance observer and Radial Basis Function Neural Networks to address unknown nonlinear dynamics and disturbances in train system. Firstly, an unknown nonlinear dynamics model, considering time-varying actuator faults, is established for the high-speed train using a multi-mass dynamics model. Then, the adaptive fast non-singular terminal sliding mode fault-tolerant controller is designed based on the multi-mass dynamics model. The radial basis function neural networks approximate the unknown nonlinear dynamics of the system, while the nonlinear disturbance observer observes the unknown disturbances. Finally, the stability of the controller is verified through Lyapunov function and its derivative. Simulation results show the effectiveness of the proposed method, exhibiting precise control and fast tracking speed. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Radial basis function networks

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Minimizing Average Job Completion Time for Multi-resource Queuing Computing Systems Using Drift-Plus-Penalty 3rd

Minimizing Average Job Completion Time for Multi-resource Q...

引用

3rd international conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

作者： Chen, Chuanxu Li, Ruiting Guan, Quansheng Shi, Zhan Zeng, Ying Zheng, Jianping School of Electronic and Information Engineering South China University of Technology Guangzhou China Electric Power Dispatch and Control Center Guangdong Power Grid Co. Ltd. Guangzhou China

ISBN: (纸本)9789819616978

The Lyapunov drift-based scheduling algorithms control the queue length to stabilize the system and maximize the throughput for multi-resource multi-queue cloud/edge systems. However, these algorithms often ignore the heterogeneity in job length, thus leading to a long delay for job processing. To this end, this paper takes the job completion time (JCT) as a penalty in the drift-plus-penalty expression to minimize the average job competition time, and proposes a Lyapunov drift-plus-time (LDPT) based scheduling algorithm for multi-resource queuing computing systems. The optimality of LDPT with respect to average JCT and queue length is analyzed. By using the Amazon EC2 to simulate, the results show that LDPT can improve average JCT and average queuing time fairness. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Scheduling algorithms

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Application of 3D geological modeling to analyse Fault-controlled hydrocarbon accumulation in complex structural zones: a case study of the northern part of qikou sag 3

Application of 3D geological modeling to analyse Fault-Contr...

引用

3rd international conference on Geographic Information and Remote Sensing Technology, GIRST 2024

作者： Chen, Yan Liu, Haitao Jiang, Zhenglong Sun, Jinghui Zhao, Changyi Wang, Jufeng Sun, Deqiang Tang, Zijun Zhang, Chunming Wu, Fengcheng School of Ocean Sciences China University of Geosciences Beijing100083 China Research Institute of Petroleum Exploration and Development Beijing100083 China Beijing Institute of Geo-Environment Monitoring Beijing100195 China Institutes of Science and Development Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781510689077

The Qikou sag forming massive of fault-type oil and gasreservoirs. Based on previous achievements and data such as three-dimensional seismic data, this article analyzes the relationship between faults and petroleum and natural gas reservoirs in the northern part of Qikou sag through three-dimensional geological modeling. The results show that the faultcontrolled reservoir model in the study area can be roughly divided into four types: synthetic fault shielding oil and gas accumulation mode, antithetic fault shielding oil and gas accumulation mode, cross-fault shielding type petroleum and gas accumulation mode, and fault reactivation control secondary oil and gas accumulation mode. This 3D structural model shows that fault-controlled reservoir characteristics in the northern part of Qikou sag in three-dimensional space. © 2025 SPIE.

关键词： Gasoline

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Revolutionizing Biomedical engineering with Microcontroller Applications: A Comprehensive Review 3rd

Revolutionizing Biomedical Engineering with Microcontroller ...

引用

3rd international conference on Intelligent Computing Techniques for Smart Energy Systems, ICTSES 2023

作者： Pawase, Chinmay D’Souza, Sandra Department of Instrumentation and Control Engineering Manipal Institute of Technology Manipal Academy of Higher Education Karnataka Manipal India

ISBN: (纸本)9789819784288

This far-reaching study paper blends bits of knowledge from selected vital papers, featuring the instrumental job of microcontrollers in raising medical care diagnostics and checking. Microcontrollers, high level coordinated circuits with implanted handling capacities, are vital apparatuses for exact information procurement, top to bottom examination, and complex control frameworks, empowering momentous advancement in biomedical designing. The reconciliation of microcontrollers has become imperative for creating inventive clinical gadgets and analytic apparatuses as medical services progress. These conservative, superior stages are sent in different applications, from wearable wellbeing screens following imperative signs to implantable gadgets controlling insulin levels and supporting cardiovascular capabilities. They likewise assume a critical part in overseeing complex information streams, guaranteeing consistent transmission and capacity of patient data. The considered papers highlight microcontroller’s adaptability and effect in the biomedical field, upgrading analytic apparatus precision and unwavering quality, encouraging patient commitment and autonomy, and further developing medical care administrations. This paper has immensely encouraged in understanding the concepts gathered during the Microcontroller course and it gives a strong research base in the field of Microcontrollers. Microcontrollers have changed medical care by propelling diagnostics and observing accuracy, effectiveness, and availability. The cooperative energy among microcontrollers and biomedical applications has developed wonderful progressions for patients and medical care suppliers. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Diagnosis

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Geometric control Methods for On-Orbit Assembly of Modular Spacecraft Cluster

Geometric Control Methods for On-Orbit Assembly of Modular S...

引用

Mechatronics, control and robotics (ICMCR), international conference on

作者： Jingxian Wang Rong Chen Yuzhu Bai Yong Zhao College of Aerospace Science and Engineering National University of Defense Technology Changsha China

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

In this paper, a cluster geometry control method is proposed for the problem of on-orbit assembly of modular spacecraft clusters. The method bases the cluster system on a manifold. A collision avoidance constraint that does not generate terminal position mutual exclusion is designed for the characteristics of the assembly problem. Assembly and task time constraints are further considered to integrate the non-convex multiple constraints with the system metric matrix. Finally, model predictive control is used to realize tracking control. Simulation results show that the method can arrive at the target position to complete the on-orbit assembly within any initial position and different fixed time constraints and achieve the purpose of energy optimization.

关键词： Space vehicles Manifolds Target tracking Self-assembly Trajectory planning Simulation Trajectory Time factors Collision avoidance Assembly

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Employing the ResNet50 and InceptionV3 Models for the Detection of Diseases in Both Strawberry Leaves and Fruit 3rd

Employing the ResNet50 and InceptionV3 Models for the Detect...

引用

3rd international conference on Trends in Electronics and Health Informatics, TEHI 2023

作者： Shadman Sakib Mahee, B.M. Fazle Rabbi, M.M. Khanom, Tasnuba Akter, Sanu Usha, Nusrat Jahan Hasan, Md. Rabby Department of Computer Science and Engineering Bangladesh University of Business and Technology Dhaka1216 Bangladesh

ISBN: (纸本)9789819739363

The study uses powerful learning methods to identify powdery mildew and leaf scorch on strawberry fruit and leaves. The suggested solution combines ResNet50 and InceptionV3 cognitive neural networks. This strategy involves collecting powdery mildew and leaf scorch datasets and improving them. ResNet50 and InceptionV3 extract discriminative features and detect powdery mildew and leaf scorch patterns. The aggregate characteristics are put into a fully connected layer and a softmax classifier for illness classification. An optimized technique adjusts the model’s hyperparameters during training for optimal classification performance. Comprehensive testing shows that the combined model beats ResNet50, InceptionV3, and other illness diagnostic approaches. Integration of information utilizing fusion approaches improves representation and illness diagnosis. Research suggests that the reinforcement learning-based approach can identify powdery mildew and leaf scorch in strawberry fruits with an accuracy rate of 98.42% and a validation rate of 99%. This technology impacts strawberry crop disease control. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Fruits

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Deep Learning Precision Farming: Identification of Bangladeshi-Grown Fruits Using Transfer Learning-Based Detection 3rd

Deep Learning Precision Farming: Identification of Banglades...

引用

3rd international conference on Trends in Electronics and Health Informatics, TEHI 2023

作者： Siddiki, Marjuk Ahmed Rony, Mohammad Abu Tareq Naim Hossain, Md. Saha, Pritom Islam, Mohammad Shariful Ahmed, Ishtiak Satu, Shoykth Shaharior Ahammad, Mejbah Nazmul Alam, Shah Md. Computer Science and Engineering Daffodil International University Dhaka Bangladesh Noakhali3814 Bangladesh Noakhali3814 Bangladesh Computer Science and Engineering Jahangirnagar University Dhaka Bangladesh Computer Science and Engineering Shaikh Burhanuddin Post Graduate College Dhaka Bangladesh Computer Science and Engineering American International University Bangladesh Dhaka Bangladesh Masters of Computer Science University Arizona State University TempeAZ United States

ISBN: (纸本)9789819739363

The dynamic potential of Convolutional Neural Networks (CNN) enhanced by Transfer Learning offers a promising avenue for object recognition within the realm of agriculture. To explore this potential in the context of Bangladeshi agriculture, this study leverages CNN enhanced by Transfer Learning to identify Bangladeshi-grown fruits from a dataset featuring 24 distinct types, including Mango, Jackfruits, and Lychee, among others. Utilizing an extensive dataset that encapsulated high-quality images of these fruits, we embarked on a comparative analysis of six advanced CNN architectures: VGG19, Xception, ResNet152V2, MobileNet, DenseNet201, and NASNetLarge. The results were illuminating. While VGG19 lagged behind with an accuracy of 48%, most models showcased impressive performance, with DenseNet201 emerging as the frontrunner at a remarkable 95% accuracy. The findings not only underscore the transformative role of Transfer Learning in optimizing CNN performance, especially when faced with limited labeled datasets, but also spotlight the applicability of these models in revolutionizing quality control and management within the Bangladeshi agricultural sector. As the demand for automated and accurate agricultural systems gains traction globally, the insights from this research offer a foundation for further exploration and application in similar contexts, demonstrating the scalability and adaptability of Transfer Learning-enhanced CNNs. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Using Sliding Mode controller to Trajectory Tracking of the Four Mecanum Wheel Mobile Robot Applied in Automotive Plants

Using Sliding Mode Controller to Trajectory Tracking of the ...

引用

Mechatronics, control and robotics (ICMCR), international conference on

作者： Tran Vo Dang Huy Bui Thanh Luan HUTECH Institute of Engineering HUTECH University Ho Chi Minh City Viet Nam Industrial Maintenance Training Center Ho Chi Minh City University of Technology (HCMUT) Ho Chi Minh City Vietnam Vietnam National University Ho Chi Minh (VNU-HCM) Thu Duc city Ho Chi Minh City Vietnam

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

This research paper proposes a mobile robot configuration tailored to optimize transportation processes for the Skoda automobile manufacturing plant. When operating in a factory, the FMWMR is subject to external disturbances and uncertainties, so the sliding mode control (SMC) method is introduced. The control law is derived by selecting an appropriate Lyapunov function based on the robot's dynamic model. Simulation results in Matlab demonstrate the effectiveness of the proposed control algorithm in enabling the robot to follow predefined trajectories.

关键词： Uncertainty Trajectory tracking Simulation Wheels Production facilities Hardware Manufacturing Mobile robots MATLAB Sliding mode control

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Development of a Soft Gripper Using Kirigami-Inspired Techniques

Development of a Soft Gripper Using Kirigami-Inspired Techni...

引用

Mechatronics, control and robotics (ICMCR), international conference on

作者： Efrem Olivio Gomes Shyang-Jye Chang Ilham Saputra Hsu-Feng Chang Department of Mechanical Engineering National Yunlin University of Science and Technology Douliu Taiwan Department of Mechanical Engineering Vocational School Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

This study introduces a soft robotic gripper inspired by Kirigami, designed to improve flexibility and adaptability for handling delicate or irregular objects. The gripper, fabricated using silicone elastomers with strategic Kirigami cuts, allows significant deformation while maintaining structural integrity. Two models were tested on various objects. Model 1 showed superior performance, while Model 2, designed for larger objects, struggled with smaller and heavier items. The gripper demonstrated excellent adaptability, securely gripping diverse objects by conforming to complex geometries. Its potential for gentle handling makes it suitable for biomedical and agricultural applications. Durability tests revealed that the 1.5 mm thickness gripper maintained performance after over 100 cycles, outperforming the 1.0 mm version, which exhibited loosening after fewer uses. Compared to conventional grippers, the Kirigamiinspired design showed enhanced flexibility, precision, and durability, making it ideal for automation tasks. Future refinements in materials and design will further improve its performance.

关键词： Fabrication Adaptation models Shape Biological system modeling Elastomers Soft robotics Object recognition Grippers Optimization Testing

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TinyML Speech Classification Embedded Ai Module for Hand Rehabilitation Device

TinyML Speech Classification Embedded Ai Module for Hand Reh...

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Mechatronics, control and robotics (ICMCR), international conference on

作者： Arkorn Numsomran Arjin Numsomran Jutarut Chaoraingern Triam Udom Suksa Pattanakarn Suvarnabhumi School Bangkok Thailand Department of Instrumentation and Control Engineering School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Department of Robotics and AI Engineering School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

Recent advancements in artificial intelligence and machine learning have significantly improved healthcare, especially in the development of assistive technologies for rehabilitation. This paper introduces a method for hand rehabilitation that utilizes the capabilities of tiny machine learning to enhance speech classification in a rehabilitation device. The proposed method employs a CNN model capable of classifying speech signals that are indicative of different hand movement patterns. Patients emit these speech signals during prescribed hand exercises, which are crucial for their rehabilitation process. The main focus of this study is on training and deploying a speech classification system that can work in the resource-limited environment of TinyML platforms. We detail the process of capturing speech data, preprocessing it, and extracting the most features relevant to different hand movements. Our results show that using TinyML to help with hand rehabilitation works. The method we came up with shows how TinyML could change the way rehabilitative devices are controlled, and it also shows us what personalized and easy-to-use rehabilitation tools might look like in the future.

关键词： Hands Training Technological innovation Tiny machine learning Medical treatment Speech recognition Transforms Speech enhancement Feature extraction Robots

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