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检索条件"任意字段=3rd International Symposium on Control Engineering and Robotics, ISCER 2024"

共 600 条记录，以下是241-250 订阅

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Research and Design of Energy-saving Vehicle Operation Based on Supercapacitor 3

Research and Design of Energy-saving Vehicle Operation Based...

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3rd international symposium on Intelligent robotics and Systems, ISoIRS 2023

作者： Zhu, Lihong Wang, Xiaoyu Liu, Jing Zhu, Yupei Fan, Shixing Southwestern Institute of Physics The Engineering &technical College Chengdu University of Technology Chengdu614000 China The Engineering &technical College Chengdu University of Technology Leshan614000 China

ISBN: (纸本)9798350339963

In order to improve the energy utilization efficiency of electric vehicles, an energy-saving operation mode of electric vehicles with power battery and super capacitor is proposed. Based on the establishment of the power battery model and the super capacitor model, the power distribution of the hybrid battery system was carried out by using the energy control strategy of bidirectional DC/DC converter combined fuzzy PID, so as to improve the energy utilization efficiency. The results show that under SCO3 condition and ADVISOR simulation, the power absorbed by the super capacitor in the fuzzy PID control strategy obtained in this paper is more than that by the logic threshold control strategy, and the current is lower than that under the logic threshold control strategy. It is concluded that the hybrid power supply system constructed in this paper can improve energy consumption. © 2023 IEEE.

关键词： Supercapacitor

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Adaptive Reduced Fuzzy Decoupling control for Lower Limb Exoskeleton with Uncertainties 3rd

Adaptive Reduced Fuzzy Decoupling Control for Lower Limb Exo...

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3rd international Conference on Advances in Information and Communication Technology, ICTA 2024

作者： Nguyen, Van-Truong Tran, Duc-Duong Le, Ngoc-Duy Dang, Van-Truong School of Mechanical and Automotive Engineering Hanoi University of Industry Hanoi Viet Nam Faculty of Engineering Technology Hung Vuong University Viet Tri Viet Nam

ISBN: (纸本)9783031809422

In this paper, an adaptive reduced fuzzy decoupling controller is developed for a lower limb rehabilitation exoskeleton robot (2-DOF) in the case of uncertainties. With decoupled control, the initial overall MIMO system is separated into a set of individual MISO subsystems for independent control. A simplified adaptive fuzzy is proposed to reduce computation time, addressing the issues of traditional fuzzy systems. The controller has good control quality, tracking the human gait motion trajectory with uncertainty. Simulation results show that the proposed controller performs better than the traditional fuzzy controller. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Exoskeleton (robotics)

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Hand Gesture Classification using sEMG Signals and Ensemble Learning 3

Hand Gesture Classification using sEMG Signals and Ensemble ...

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3rd IEEE international Conference on Intelligent Techniques in control, Optimization and Signal Processing, INCOS 2024

作者： Chandran, Ranjeesh R Devaraj, D. Ashok, Saurav Shaji, Donfred Saju, Sam K Adishankara Institute of Engineering and Technology Department of Robotics and Automation Kerala Kalady India Kalasalingam Academy of Research and Education Department of Electronics and Electrical Technology Tamil Nadu Srivilliputhur India Adishankara Inst. of Eng and Tech. Department of Robotics and Automation Kerala Kalady India

ISBN: (纸本)9798350361186

Electromyographic signals offer details on a muscle activity of a person. In the case of hand movements various combinations of forearm muscles must be activated in order to carry out each gesture, which results in unique electrical patterns. On the other hand, identifying the motion being executed is made possible by the examination of these patterns of muscle activation, which are captured by EMG signals. This article presents a novel implementation on hand gesture classification utilizing Electromyography (EMG) signals recorded through a MYO Thalmic bracelet. The dataset consists of raw data collected from 36 subjects, each executing a series of static hand gestures. The classification model employed for this study is an ensemble of decision trees, achieving an impressive validation accuracy of 98.0% and a test accuracy of 98.1 %. The article outlines the dataset details, recording methodology, and provides an in-depth analysis of the model architecture, hyperparameters, and training results. © 2024 IEEE.

关键词： Decision trees

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A Data-driven Estimation Algorithm for Vehicle Side-Slip Angle 3

A Data-driven Estimation Algorithm for Vehicle Side-Slip Ang...

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3rd international symposium on Intelligent robotics and Systems, ISoIRS 2023

作者： Wang, Yonghui Deprizon, Syamsunur Ucsi University Faculty of Engineering Technology and Built Environment Department of Civil Engineering Kuala Lumpur Malaysia

ISBN: (纸本)9798350339963

The vehicle side-slip angle (VSA) is an important state parameter of vehicle dynamics, which can judge the stability and safety of the current state of a vehicle. Improving its estimation accuracy will contribute to the research on vehicle control theory. However, directly measuring the VSA is too costly for production vehicles, so it is generally estimated. This paper proposes a data-driven VSA estimation model that does not rely on high-precision sensors and that does not need strict vehicle dynamics and tire models. It is only necessary in the early development stage to rapidly estimate VSA by obtaining variable data that affects VSA, such as yaw speed, vehicle speed, and lateral acceleration. Verification of vehicle test data shows that the VSA estimate has strong robustness to the impact of vehicle model deviation and noise, and the proposed model can accurately estimate the VSA of high and low adhesion roads under control parameters. © 2023 IEEE.

关键词： control system synthesis

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Waste Sorting Automation with Visual Sensor and RFID 3

Waste Sorting Automation with Visual Sensor and RFID

引用

3rd international Conference on Advanced Electrical engineering, ICAEE 2024

作者： Seray, Seif Eddine Bey, Ishak Akli, Isma University of M'hammed Bouguerra Department of Control and Power Boumerdes Algeria Center for Development of Advanced Technologies Robotics and Industrial Automation Division Algiers Algeria

ISBN: (纸本)9798350349351

The quantity of domestic wastes is constantly increasing, resulting on overload of wastes. Recycling became imperative for ecologic and economical considerations in order to apply circular economy rules. In general, humans are recruited in waste sorting plants for performing the dangerous and tedious sorting tasks. The automation is, thus, necessary. This paper deals with the problem of waste sorting automation. The proposed solution consists of waste recognition and classification using YOLOv8, and human presence detection using RFID (Radio frequency Identification) tags. The proposed solution is validated in simulation. The virtual robot performs a task in order to simulate the behavior of a real robot with high fidelity, depending on the information coming from the RFID tags and a visual sensor. © 2024 IEEE.

关键词： Radio frequency identification (RFID)

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Raspberry Pi based Color and Shape Detection Bot 3

Raspberry Pi based Color and Shape Detection Bot

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3rd IEEE international Conference on Intelligent Techniques in control, Optimization and Signal Processing, INCOS 2024

作者： Pon Pushpa, S. Ewins Mariammal, K. Kumar, Dharavath Sai Mohamed Nishar, M. Siddharth, K. Sundhara Ganesh, J. College of Engineering Guindy Anna University Department of Ece Chennai India Madras Institute of Technology Anna University Department of Electronics Engg. Chrompet Chennai India

ISBN: (纸本)9798350361186

This paper introduces an innovative sorting system that leverages, advanced image processing capabilities, particularly focusing on color and shape detection, integrated into a robotic platform. The cost-effective solution, utilizes the Raspberry Pi single-board computer to maximize computational power, achieving efficient object sorting. The system excels in identifying, sorting, and processing objects, based on color and shape attributes, with added functionality for obstacle detection. Through seamless integration of Raspberry Pi with Python programming, and advanced image processing, the project showcases the potential of this approach, in addressing challenges in automation and robotics. This technology holds promise for future applications, in medical imaging and pharmaceutical settings, offering efficient analysis and sorting based on color and shape characteristics. © 2024 IEEE.

关键词： Color

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The Simulation of AC Power Grid Detection By MEMS Microcoils 3

The Simulation of AC Power Grid Detection By MEMS Microcoils

引用

3rd international symposium on Sensor Technology and control, ISSTC 2024

作者： Chen, Xiaolong Wang, Pengyu Sun, Xuecheng Shanghai University Microelectronic R&D Center Shanghai University School of Mechatronic Engineering and Automation Shanghai China

ISBN: (纸本)9798331541637

Smart grid monitoring plays a pivotal role in optimizing power distribution and minimizing energy wastage, especially relying on current detection methods. The traditional current detection device was bulky, costly and inconvenient to install. This paper was aim to study the theoretical feasibility of alternating current detection of based microcoil fabricated by MEMS technology for Power grid monitoring. The power transmission line and microcoil model was established, and the influence of different coil arrangement on the detection current was studied. The simulation results verified that the detection of alternating power grid based on MEMS microcoil was feasible. Driven by an alternating current of 500 amperes at a frequency of 50 Hertz, the microcoils arranged in an array can induce a current of up to 68 microampere at a certain distance, and the detection performance can be further improved by adjusting the array and placement mode. The results of simulation calculations provided a certain theoretical guidance for the design and fabrication of current sensors based on MEMS microcoils. © 2024 IEEE.

关键词： Power grids

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Design and Implement of a Super-Twisting ESO-Based Impedance control for Lower Limb Exoskeleton 3

Design and Implement of a Super-Twisting ESO-Based Impedance...

引用

3rd international Conference on Mechatronics and Automation Technology, ICMAT 2024

作者： Zhang, Wenhao Ji, Pingxin Song, Peng Liu, Hao Li, Qiang Mo, Xinmin Northwest Institute of Mechanical and Electrical Engineering Shaanxi Xianyang712099 China Department of Mechanical and Engineering Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781643685649

This brief proposes a super-twisting ESO-based impedance control for lower limb exoskeleton to promote the human-machine interaction-based coordination and stability with the unmodeled tire dynamics and external perturbations into consideration. The kinetics both in hip and knee joint is constructed and expected to match the authentic angle curve which depicts the moving organization in real-time. Then, by insetting a generalized super-twisting algorithm, the super-twisting ESO (STESO) is introduced to capture the immeasurable entire disturbances by utilizing the angle state merely. Subsequently, by quoting the impedance control theory, the global terminal angles can be calculated and adjusted basing the human-interaction force, even on the environment mapping. Finally, some theoretical analysis and simulations are collected and provided to demonstrate the correctness and effectiveness for proposed method. © 2024 The Authors.

关键词： Exoskeleton (robotics)

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From Chaos to control: Leveraging Multi-Expert Strategies for Predictive Accuracy in Autonomous Systems 3

From Chaos to Control: Leveraging Multi-Expert Strategies fo...

引用

3rd international Conference on Mechatronics and Automation Technology, ICMAT 2024

作者： Grigoriev, D.A. Musaev, A.A. Sokolov, B.V. Saint-Petersburg Russia ITMO University Saint-Petersburg Russia St. Petersburg Federal Research Center Russian Academy of Sciences Saint-Petersburg Russia

ISBN: (纸本)9781643685649

This paper addresses the challenge of predicting chaotic behavior in automatic control systems and robotics, especially in unstable environments. Chaotic elements in observational data diminish the effectiveness of traditional statistical methods, necessitating novel predictive approaches. We propose a predictive framework based on a multi-expert data analysis model for control applications. Preliminary predictions are generated by software experts as weak classifiers, while a supervising expert consolidates these into a final decision. This approach resembles stacking algorithms used in ensemble decision-making. Our methodology enhances predictive accuracy in chaotic environments, leveraging the structural redundancy of multi-expert systems for improved robustness. Empirical results indicate that it strengthens decision-making in unpredictable scenarios, paving the way for future research on managing chaotic dynamics in automatic control and robotics. © 2024 The Authors.

关键词： Expert systems

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Research on Encrypted Network Traffic Recognition Based on Neural Architecture Search Network 24

Research on Encrypted Network Traffic Recognition Based on N...

引用

3rd international symposium on robotics, Artificial Intelligence and Information engineering, RAIIE 2024

作者： Wang, Yongsheng Wei, Xiaoxu Chen, Zhenwei Dong, Bin School of Information Engineering Wuhan University of Technology Wuhan430070 China School of Automotive Engineering Wuhan University of Technology Wuhan430070 China Wuhan Greenet Information Service Co. Ltd. Wuhan430070 China

ISBN: (纸本)9798400718311

Encrypted network traffic not only protects user privacy and information security, but also brings hidden dangers to network security. It is of great significance for network maintenance and operation to identify and classify the characteristics of encrypted network traffic effectively. This paper proposes a mobile application identification and classification engine based on neural architecture search network, which adopts NASNet network structure and can realize the identification of mobile application encrypted traffic from the perspective of OSI network layer. The engine can further perceive the service quality of users' Internet experience, and then evaluate the overall quality of the network quantitatively. The experimental results show that the NASNET-based neural network can identify encrypted traffic with an average accuracy of 99%, and has the characteristics of high accuracy rate, high recall rate and high F1-score, which can effectively deal with the security of encrypted traffic in mobile applications. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Network layers

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