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检索条件"任意字段=Proceedings of the 2019 2nd International Conference on Control and Robot Technology"

共 3960 条记录，以下是31-40 订阅

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proceedings - 2019 2nd international conference of Intelligent robotic and control Engineering, IRCE 2019

Proceedings - 2019 2nd International Conference of Intellige...

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2nd international conference of Intelligent robotic and control Engineering, IRCE 2019

ISBN: (纸本)9781728141923

The proceedings contain 33 papers. The topics discussed include: hydrodynamic analysis on the shape of bionic fish based on CFD;supervisory control of discrete event systems in manufacturing industry;integrated production system using ERP and MES;upper-level task ontology for generic ontology verbalization;coordinated optimization control of regional traffic signals based on vehicle average delay model;a scan matching method for quadruped robots in outdoor environment;design of double closed loop control system for beam supply;elitist reinforcement strategy for differential evolution;and a brain computer interface for attention study.

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ICETM 2019 - proceedings of 2019 2nd international conference on Education technology Management

ICETM 2019 - Proceedings of 2019 2nd International Conferenc...

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2nd international conference on Education technology Management, ICETM 2019

ISBN: (纸本)9781450376297

The proceedings contain 21 papers. The topics discussed include: investigating the Dunning-Kruger effect among students within the contexts of a narrative-centered game-based learning environment;study on the case-based teaching method in the circuit principle course under emerging engineering education;teachers' meaning formation and mental concept representation of inclusion;design of a multicriterion model with a diffuse hierarchical analysis process - FAHP, for the selection of suppliers in a mobile cellular telecommunications company;the effect of operations risk on cooperation efficiency of industry-university-research knowledge innovation alliance in China;and trial to increase motivation on programming by using hardware control functions in the AT visual programming environment.

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proceedings of the 2019 2nd international conference on Power and Embedded Drive control, ICPEDC 2019

Proceedings of the 2019 2nd International Conference on Powe...

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2nd international conference on Power and Embedded Drive control, ICPEDC 2019

ISBN: (纸本)9781728124148

The proceedings contain 103 papers. The topics discussed include: techno-economic analysis of rooftop solar PV system by variation in PV Module capacity;experimental and numerical studies on a cross axis wind turbine;community-based biogas supply system for village Jalera at Baran District in Rajasthan;cyber security in smart grid: challenges and solutions;analysis and implementation of HOT standby operation of variable frequency drives;design development of robotic arm for medical surgery;design and implementation of enhanced PID controller in embedded platform for real-time applications;and optimization of wind thermal coordination dispatch using flower pollination algorithm.

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Modeling and Robust control for Power Insurance Assessment SCARA robots Using RAG Retrieval-Augmented Techniques

Modeling and Robust Control for Power Insurance Assessment S...

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Smart Grid and Artificial Intelligence (SGAI), international conference on

作者： Miao Hong Shebing Liu Kuaiqin Zhao Lei Shi State Grid Anhui Electric Power Co. Ltd. Huaibei Wante Technology & Commerce Co. Ltd. Hefei China State Grid Anhui Electric Power Co. Ltd. Hefei China State Grid Huaibei Electric Power Supply Company Huaibei China State Grid Chizhou Electric Power Supply Company Chizhou China

ISBN: (数字)9798331518806

ISBN: (纸本)9798331518813

To address the challenges faced by SCARA (Selective Compliance Assembly robot Arm) robots in power insurance evaluation and claims processing, particularly in accurately and rapidly tracking desired motion trajectories within specified joint angle ranges, this paper presents an integrated approach that combines an improved optimal robust control algorithm with Retrieval-Augmented Generation (RAG) technology. Initially, state transformation techniques are employed to ensure that the controlled output meets inequality constraints, thereby keeping the robot joints within the preset angle ranges and mitigating deviations caused by external disturbances. The control system integrates an optimal robust control algorithm comprising two core components: a nominal controller responsible for stabilizing the nominal robot system, and a robust controller based on the Lyapunov method designed to address tracking performance issues due to parameter uncertainties. The RAG technology plays a pivotal role by retrieving and generating supporting information from relevant data, significantly enhancing the adaptability and robustness of the control strategy. The stability of the system under uncertain conditions is verified using the Lyapunov min-max approach. The efficacy of the proposed algorithm is demonstrated through simulations and experimental validation on the SCARA robot platform. The proposed integrated method provides an effective solution for high-precision control of SCARA arms in complex environments and demonstrates potential for improving automation levels in power insurance evaluations, offering new insights and references for similar robotic control challenges.

关键词： Robust control Uncertain systems Tracking Insurance Arms Manipulators control systems Trajectory Time factors robots

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2nd international conference on Computer Information Science and Application technology, CISAT 2019 - 5. control System and Technical Management

2nd International Conference on Computer Information Science...

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2nd international conference on Computer Information Science and Application technology, CISAT 2019

The proceedings contain 419 papers. The topics discussed include: analysis of the relationship between international service trade and economic growth based on VAR model;building a reference model for a manufacturing execution system (MES) platform in an industry 4.0 context;study on multi-objective dynamic optimization method for architectural engineering based on BIM;research on LDPC coding cooperative system based on intelligent joint iterative decoding;precise unmanned aerial vehicle visual positioning based on neural network;non-linear regression method for instability problems in haptic rendering system;airborne gateway: key technology of earth observation system in the space-air-ground integration network;airborne gateway: key technology of earth observation system in the space-air-ground integration network;and research on the propagation characteristics of social events in the context of micro-media.

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Modeling and Robust control for Modules in Electric Power Insurance Loss Assessment and Claims robot

Modeling and Robust Control for Modules in Electric Power In...

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Smart Grid and Artificial Intelligence (SGAI), international conference on

作者： Bin Wu Li Zhang Yan Chen Juan Zhang Di Zhang State Grid Anhui Electric Power Co. Ltd. Huaibei Wante Technology & Commerce Co. Ltd. Hefei China State Grid Anhui Electric Power Co. Ltd. Hefei China State Grid Chizhou Electric Power Supply Company Chizhou China State Grid Anhui Information & Telecommunication Branch Hefei China

ISBN: (数字)9798331518806

ISBN: (纸本)9798331518813

This study presents a new robust model-based control method to reduce the effects of variable system parameters and workload on the performance of power insurance claim assessment robots' articular *** combines PID control with robust compensation and model-based strategies to improve precision in uncertain conditions. The controller is carefully designed according to the dynamic model and includes a Lyapunov-based component to handle uncertainties in system dynamics. This strategy, enhancing traditional PID or reconfiguring robust control, is easy to apply and provides clear advantages. Theory shows the controller ensures stability and reliability through uniform ***, a Matlab-based simulation platform has been used to create a controller prototype, simplifying development and debugging. Finally, simulations confirm the feasibility and effectiveness of the proposed control method.

关键词： Robust control Uncertainty Heuristic algorithms Insurance Power system stability Mathematical models Stability analysis Robustness PD control Mechanical systems

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Detection and Identification of Power Quality Disturbance Signals in New Power System Based on Quantum Classic Hybrid Convolutional Neural Networks 2nd

Detection and Identification of Power Quality Disturbance ...

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2nd international conference on Data Security and Privacy Protection, DSPP 2024

作者： Li, Yue Li, Xinhao Jia, Haopeng Liu, Anjiang Wang, Qingle Hao, Shuqing Liu, Hao Electric Power Research Institute of Guizhou Power Grid Co. Ltd. Guiyang550002 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China School of Electrical and Electronic Engineering North China Electric Power University Beijing102206 China

ISBN: (纸本)9789819785452

With the rapid development of modern power systems, power quality disturbances are a growing concern, impacting system reliability. Effective detection and identification of PQDs in new distribution systems with high renewable energy integration are crucial. In this paper, we propose a quantum-classical hybrid convolutional neural network for detecting and identifying power quality disturbances using a quantum-classical hybrid convolutional neural network (PQDs-QC-CNN). The PQDs-QC-CNN model includes quantum convolutional layers, fully connected layers, and softmax regression. The proposed PQDs-QC-CNN achieves a certain speed with the time complexity of O(poly(N)) and the space complexity of O(N), where N is the number of qubits. Compared to classical convolutional neural networks, PQDs-QC-CNN leverages quantum algorithms, offering the advantage of lower computational complexity. According to the IEEE Std 1159-2019 standard, the experimental results of our PQDs-QC-CNN achieves 100% detection accuracy. Following the seven types of single disturbance signals, the identification is 99.25%. PQDs-QC-CNN represents a significant exploration of the application of quantum algorithms in the power system. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Autonomous Firefighting robot: Design and Implementation for Hazardous Environment Operations

Autonomous Firefighting Robot: Design and Implementation for...

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Advanced Innovations in Smart Cities (ICAISC), international conference on

作者： Nisrin Amer Alsaiari Saman Iftikhar Leen Hassan Ibrahim Amnah Hezam Alshehri Sarah Abdullah Hadad Amjad Hassan Alkhudaydi Faculty of Computer Studies (Applied Computer Science) Arab Open University Jeddah Saudi Arabia Faculty of Computer Studies (information security) Arab Open University Jeddah Saudi Arabia Faculty of Computer Studies (ITC) Arab Open University Jeddah Saudi Arabia Faculty of Computer Studies (Computer Science) Arab Open University Jeddah Saudi Arabia

ISBN: (数字)9798331506995

ISBN: (纸本)9798331507008

This research focuses on the development of a robotic system designed to assist firefighters in assessing hazardous environments, aiming to improve safety and operational efficiency. The prototype, modeled as a car, autonomously evaluates fire-affected areas using Arduino microcontroller technology, integrating temperature and smoke sensors to monitor critical parameters like heat levels and smoke density in real-time. An ultrasonic sensor ensures precise navigation by detecting obstacles and dynamically adjusting movement to prevent collisions. Powered by high-capacity batteries, DC motors, and a DC driver, the robot demonstrates reliable mobility in all directions. A Bluetooth module facilitates seamless wireless communication with a control program developed in Visual Studio using C#, enabling remote operation and environmental monitoring. The robot also features a buzzer for auditory alerts and multi-color LED indicators to provide clear visual signals about environmental conditions to users and bystanders. The prototype successfully implements these functionalities, showcasing its potential as a preliminary model.

关键词： Temperature sensors Visualization Service robots Navigation Fires robot sensing systems Acoustics Sensors Collision avoidance Gas detectors

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RCAE 2019 - proceedings of the 2019 The 2nd international conference on robotics, control and Automation Engineering - 2nd international conference on Advanced Mechanical and Electrical Engineering, AMEE 2019

RCAE 2019 - Proceedings of the 2019 The 2nd International Co...

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9th international conference on Communication and Network Security, ICCNS 2019

The proceedings contain 30 papers. The topics discussed include: a web services testing approach based on difference measurement and adaptive random testing;android malware detection combined with static and dynamic analysis;semantic-based malware behavior description: past and future;an automatic testing platform for object-oriented software based on code coverage;secure email login based on lightweight asymmetric identities;location privacy protection scheme based on location services;mobile phone number privacy scheme based on lightweight hash mapping;a method of detecting the abnormal encrypted traffic based on machine learning and behavior characteristics;an efficient, secure and reliable search scheme for dynamic updates with blockchain;and differentially private graph clustering algorithm based on structure similarity.

关键词： Machine learning

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Optimizing Industrial Etching Processes for PCB Manufacturing: Real-Time Temperature control Using VGG-Based Transfer Learning 2nd

Optimizing Industrial Etching Processes for PCB Manufacturin...

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2nd international conference on Intelligent Manufacturing and robotics, ICIMR 2024

作者： Luo, Yang Jagtap, Sandeep Trollman, Hana Garcia-Garcia, Guillermo Liu, Xiaoyan P.P. Abdul Majeed, Anwar School of Intelligent Manufacturing Ecosystem Xi’an Jiaotong-Liverpool University Suzhou Taicang215400 China Division of Engineering Logistics Lund University Lund Sweden Sustainable Manufacturing Systems Centre Cranfield University CranfieldMK43 0AL United Kingdom School of Business University of Leicester LeicesterLE2 1RQ United Kingdom Department of Chemical Engineering Faculty of Sciences University of Granada Avda. Fuentenueva S/N Granada18071 Spain School of Engineering and Technology Sunway University Selangor Darul Ehsan Bandar Sunway47500 Malaysia

ISBN: (纸本)9789819639489

Accurate temperature control in Printed Circuit Board (PCB) manufacturing is essential for maintaining high-quality etching results. Automated monitoring using machine vision and deep learning offers an effective approach for this task. This study investigated a feature-based transfer learning technique for classifying temperature readiness in infrared images of the etching process. The captured dataset containing 470 ‘Production-Ready’ and 480 ‘Not-Ready’ infrared images of the etchant tank was utilized. Pre-trained Visual Geometry Group (VGG) Convolutional Neural Network (CNN) models, specifically VGG16 and VGG19, were employed to extract discriminative features from these images. Logistic Regression (LR) classifiers were then trained on these features to classify the infrared images. The performance of the VGG16-LR and VGG19-LR pipelines was evaluated on training, validation, and test sets using a 60:20:20 split. While both pipelines achieved 100% accuracy on the training sets, the VGG19 pipeline showed exceptional performance, achieving a validation accuracy of 95%, and a test accuracy of 99%. The VGG16 pipeline also demonstrated robust performance, achieving 96% accuracy on both the validation and test sets. Considering the dimensions and the overall efficiency of the pipeline, it was determined that the VGG19-LR model was appropriate for the captured dataset. The high accuracy indicates that transfer learning is suitable for categorizing temperature fluctuation in infrared thermography, as opposed to training a deep neural network from scratch. Computer vision and deep learning provide automated and precise temperature management during the etching process, leading to enhanced efficiency in PCB manufacturing. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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