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检索条件"任意字段=7th International Conference on Advanced Algorithms and Control Engineering, ICAACE 2024"

共 513 条记录，以下是61-70 订阅

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Optimization of Clamping Die Axis control Strategy for Pipe Bending Machine Based on DEFORM-3D Finite Element Analysis 7

Optimization of Clamping Die Axis Control Strategy for Pipe ...

引用

7th international conference on advanced algorithms and control engineering, icaace 2024

作者： Zhang, Liang Zhang, Qingzhu Liao, Chenghao Li, Lianghong Wei, Yulan Li, Bing School Of Engineering Huzhou University Huzhou China Zhejiang Heliang Intelligent Equipment Co. Ltd. Huzhou China

ISBN: (纸本)9798350361445

To solve the problem of precise control of clamping die during the pipe bending process, this study utilizes DEFORM-3D software to perform finite element analysis on the pipe bending process of φ 65 × 3 pipes. the torque simulation values of the clamping die during the pipe bending process are investigated, and their comparison with theoretical values ultimately reveals a good agreement, confirming the reliability of the model. Based on the optimal values for the clamping die axis retention torque, a control strategy is proposed, combining servo motor position control with torque control to optimize the clamping die axis. this approach effectively addresses issues in actual production where excessive clamping force leads to markings and deformation of the pipes. this study presents a new control method for precise bending forming of pipes, offering important theoretical and practical value for enhancing the bending performance and forming quality of pipe bending machines. © 2024 IEEE.

关键词： Finite element method

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Grasp control Method for Robotic Manipulator Based on Federated Reinforcement Learning 7

Grasp Control Method for Robotic Manipulator Based on Federa...

引用

7th international conference on advanced algorithms and control engineering, icaace 2024

作者： Wang, Yue Zhong, Shida Yuan, Tao College Of Electronics And Information Engineering Shenzhen University State Key Laboratory Of Radio Frequency Heterogeneous Integration Shenzhen China Shenzhen University Guangdong-Hong Kong Joint Laboratory For Big Data Imaging And Communication Shenzhen China

ISBN: (纸本)9798350361445

With development of mobile edge computing (MEC) and the Artificial Intelligent Internet of things (AIoT), how to use intelligent devices to better apply to industrial scenarios has become a critical factor in promoting industry to reduce costs, increase efficiency, and enable development. In this paper, we analysis the problem of robotic manipulators working in dynamic environments and propose a model based on federated reinforcement learning (FRL) to control robotic manipulator grasping. In the proposed FRL framework, the optimal control policy is learned independently by multiple agents on their respective AIoT devices. Also, we use federated learning to ensure the safety of data and improve the reward function to accelerate the learning of model. We evaluate the performance of the proposed method and compare it with the traditional method based on RL. the experimental results show that proposed algorithm significantly improves the model training convergence speed by about 64% and the task average reward performance index by about 36% compared with baseline. © 2024 IEEE.

关键词： Reinforcement learning

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Research and Implementation of Fuzzy Test Method Based on Multi-armed Bandit 7

Research and Implementation of Fuzzy Test Method Based on Mu...

引用

7th international conference on advanced algorithms and control engineering, icaace 2024

作者： Qin, Yiwen Jiang, Jincheng Li, Changzhi Lu, Futao Deng, Kaiwen Yang, Zengyu Network Control Lab Chongqing University Of Posts And Telecommunications Chongqing China

ISBN: (纸本)9798350361445

thereare a lot of vulnerabilities in industrial control protocols due to rothole in protocol implementation and problems with exception handling of function codes. In order to solve low effectiveness of generating test cases and the inability to adjust the test case generation by feedback from the device, fuzzy test method based on multi-armed bandit(MAB) algorithm is proposed. Firstly, the protocol unit is divided into feature sets and a matrix model is established by deeply analyzing the protocol specification, so as to initially preprocess the input data set. Secondly, the protocol constraint rule set is constructed to filter the invalid cases that violate the protocol specification. Finally, the exploration and utilization phase of the model is customized by using multi-armed bandit algorithm and fuzzy test method to increase the selection probability of mutation factors that easily trigger vulnerabilities, and establish a test case queue to save the fuzzy test cases, moreover, the probability distribution is adjusted by using the feedback of test *** results show that this method improves the abnormality rate of the test system, and the vulnerability mining ability is significantly improved. © 2024 IEEE.

关键词： Probability distributions

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Development of a Machine Learning-Based Robotic System for Medical-Targeted Drug Delivery System

Development of a Machine Learning-Based Robotic System for M...

引用

8th National conference on New Trends in Information and Communications Technology Applications, NTICT 2024

作者： Simango, Doubt Manyanye, Trish Aldhaibani, Jaafar A. Yahya, Abid Mushiri, Tawanda Ndaimani, Augustine Department of Mechatronic Engineering School of Engineering Sciences and Technology Private Bag Off-Chirundu Road Chinhoyi7724 Zimbabwe College of Engineering University of Information Technology and Communication Baghdad Iraq Botswana International University of Science and Technology Private Bag 16 Palapye Botswana Department of Industrial and Mechatronics Engineering Faculty of Engineering and the Built Environment University of Zimbabwe 630 Churchill Avenue Mt Pleasant Harare Zimbabwe Department of Biomedical Informatics and Biomedical Engineering University of Zimbabwe 630 Churchill Avenue Mt Pleasant Harare Zimbabwe

ISBN: (纸本)9783031870750

Medical robotics is a field that combines engineering and artificial intelligence to create robotic systems used in healthcare. this study aims to delve into the exciting field of developing medical-targeted drug delivery systems, which hold immense potential for revolutionizing how we administer therapeutic substances. By precisely delivering drugs to specific sites within the body, these innovative systems offer improved treatment outcomes, reduced side effects, and enhanced patient compliance. therefore, an image processing algorithm for visible target detection was designed, a system to determine the coordinates of the exact location of identified regions of the target was developed, and a trajectory plan for the robotic arm end effector for precise drug delivery was also designed. the integration of robotic systems into MRI scanners, the development of image processing algorithms, and also real-time feedback control systems are mechatronics-based processes. Medical image navigation technology has many uses in minimally invasive robots, mainly image acquisition techniques such as Magnetic Resonance Imaging (MRI) to acquire equivalent image data;however, medical imaging techniques have inefficient visibility in robotic-assisted surgeries of small and confined incisions. therefore, image processing methods are applied to precisely regulate the operation’s location and visibility and improve the procedure’s efficacy, accuracy, and safety. To develop an advanced medical-targeted drug delivery system. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： End effectors

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An Improved Underwater Object Detection Method Based on YOLOv5 7

An Improved Underwater Object Detection Method Based on YOLO...

引用

7th international conference on advanced algorithms and control engineering, icaace 2024

作者： Wang, Gang Zhuang, Sheng Zhao, Qiang College Of Mechanical And Control Engineering Jilin Communications Vocational And Technical College Changchun China College Of Mechanical And Control Engineering Baicheng Normal University Baicheng China College Of Information And Control Engineering Jilin Institude Of Chemical Technology Jilin China

ISBN: (纸本)9798350361445

To address the issue of lower accuracy in underwater biological recognition with the YOLOv5s model, we introduce several enhancements, including the Convolutional Block Attention Module (CBAM), Pyramid Pooling Module (PPM) structure, Receptive Field Block (RFB) module, and the Complete IoU (CIOU) loss function. Subsequently, we introduce the RFB module at the model's neck, effectively enhancing the model's perception of the receptive field and extracting multi-scale, rich feature information to improve recognition accuracy. Finally, the incorporation of the CIOU loss function mitigates issues related to gradient explosion or vanishing during model *** results demonstrate that our improved YOLOv5s-Ours model exhibits notable improvements in F1 score (%), precision (P %), recall (R %), and mean average precision (mAP %), with respective increases of 1.25%, 0.19%, 2.01%, and 2.28%. © 2024 IEEE.

关键词： Object detection

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Optimal PD Angle control Combined with Anti-saturation Filter for DC Motor via Root Locus Analysis 7

Optimal PD Angle Control Combined with Anti-saturation Filte...

引用

7th international conference on Automation Electronics and Electrical engineering

作者： Li, Yige Northeastern Univ Sino French Inst Engn Shenyang 110819 Peoples R China

ISBN: (纸本)9798350377040;9798350377033

Accurate angular control of DC motors is crucial in numerous industrial applications. the proportional-integral-derivative (PID) controller is widely employed for this purpose. However, conventional PID tuning techniques, such as trial-and-error, frequently result in overshoot and saturation issues, which degrade system performance. While advanced optimization algorithms like Genetic algorithms and Particle Swarm Optimization enhance tuning precision, they demand stringent initial parameter settings and are unnecessarily complex for straightforward scenarios. this paper introduces a tuning method for proportional-derivative (PD) control using the root locus analysis. A filter is incorporated to mitigate saturation effects. the proposed method simplifies the tuning process, offering a low-complexity solution while ensuring optimal performance. A rigorous mathematical analysis is presented, including the application of transfer functions and the development of mathematical models, allowing adaptation to various scenarios. Simulation results in MATLAB confirm that the proposed approach enables parameter tuning with zero overshoot under non-saturation conditions. this research contributes a novel optimization strategy for DC motor angular control, reducing system complexity while enhancing robustness. the method is applicable to real-time industrial control systems and has the potential for wider use in motor control, providing substantial practical relevance.

关键词： DC motor control PD controller root locus filter transfer function

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Congestion control and Routing Optimization for LEO Satellite Networks Based on Deep Reinforcement Learning 7

Congestion Control and Routing Optimization for LEO Satellit...

引用

7th international conference on Automation Electronics and Electrical engineering

作者： Tang, Keyi Sun, Xuebin Beijing Univ Posts & Telecommun Beijing Peoples R China

ISBN: (纸本)9798350377040;9798350377033

this paper presents a routing optimization method for LEO networks using DRL. the experimental results demonstrate that the enhanced DQN-based algorithm is effective in optimizing load balancing and alleviating routing congestion. these findings provide strong support for the performance optimization and routing decisions of LEO networks. It can be observed that the average link utilization trained by the MADQN-MQ algorithm is lower, indicating better load conditions. Compared to the Dijkstra and MADQN algorithms, it has a certain advantage in addressing the load balancing issue in the network.

关键词： congestion control deep reinforcement learning LEO satellite networks routing routing optimization

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Enhancing Microgrid Sustainability through Adaptive Energy Management Using Intelligent control algorithms 7

Enhancing Microgrid Sustainability Through Adaptive Energy M...

引用

7th international conference on Energy Conservation and Efficiency, ICECE 2024

作者： Noor, Javeria Dong, Mi Tariq, Zain Central South University School of Automation Changsha China University of Engineering and Technology Department of Electrical Engineering Taxila Pakistan

ISBN: (纸本)9798350370898

this study introduces an advanced control algorithm tailored for a bipolar DC microgrid to optimize the distribution of power among key resources, including wind energy generators (WEGs), solar photovoltaic (PV) systems, and battery energy storage (BES) units. the developed algorithm, a combination of intelligent load sharing and real-time monitoring, dynamically allocates power based on immediate demand. In this context, the main contributors of microgrid, such as wind energy, solar panels, and battery storage, collaborate seamlessly to share the load efficiently. By prioritizing renewable sources and adapting the battery's charge or discharge to meet diverse loads, this control algorithm ensures not only stability, but also sustainable and optimal performance in bipolar DC microgrid operations. © 2024 IEEE.

关键词： Power management

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Research on the control Method of Electric Vehicle Charging, Discharging, and Storage Integrated Station for Diversified Vehicle-Grid Interaction 7

Research on the Control Method of Electric Vehicle Charging,...

引用

7th international conference on Automation Electronics and Electrical engineering

作者： Zeng, Zhili Lang, Jie Jin, Xin Zhang, Chao Shenzhen Dingwang Technol Co Ltd Shenzhen Peoples R China

ISBN: (纸本)9798350377040;9798350377033

With the rapid increase in the number of electric vehicles, the interaction between electric vehicles and the power grid has become a core issue in modern energy management. this paper proposes an optimized control strategy for an electric vehicle charging, discharging, and storage integrated station aimed at diversified vehicle-grid interaction. the strategy comprehensively considers the charging, discharging, and energy storage needs of electric vehicles and designs an efficient control model based on genetic algorithms, simulated annealing algorithms, and neural network technologies. through multi-scenario simulation analysis, the effectiveness and feasibility of the proposed method in improving charging and storage efficiency, balancing loads, and enhancing system robustness are verified. this research not only provides theoretical support for the collaborative management of electric vehicles and the power grid but also lays the foundation for the future development of smart grids.

关键词： Electric vehicles charging and storage integrated station vehicle-grid interaction

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Sensorless control of IPMSM in Full Speed Range 7

Sensorless Control of IPMSM in Full Speed Range

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7th international conference on Energy, Electrical and Power engineering (CEEPE)

作者： Gu, Guanghao Yin, Dejun Nanjing Univ Sci & Technol Sch Mech Engn Nanjing Peoples R China

ISBN: (纸本)9798350375794;9798350375800

With the aim of controlling interior permanent magnet synchronous machine (IPMSM) throughout the whole speed range, a combined sensorless control approach is proposed to get beyond the limitations of a single sensorless control method. As the speed increases, an advanced sliding mode observer (SMO) technique is applied to accurately determine the location of the rotor. this approach effectively addresses the issue of frequent high frequency disturbances encountered with conventional SMO methods. At lower speeds, a high frequency square wave injection method (HFSWI) is utilized for rotor site estimation. this method boasts improved system dynamics and requires less reliance on low pass filters when compared to traditional high frequency injection methods (HFI). Additionally, a weighted average switching algorithm is applied in the combined control area to ensure a seamless transition between control strategies.

关键词： IPMSM SMO High frequency Square Wave Injection Full Speed Range Weighted Switching Algorithm

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