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

共 3924 条记录，以下是1701-1710 订阅

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Safety Design of Uncontained Engine Rotor Failure for Civil Aircraft Primary Flight control System 3

Safety Design of Uncontained Engine Rotor Failure for Civil ...

引用

2023 3rd international conference on Mechatronics Technology and Aerospace engineering, ICMTAE 2023

作者： Wang, Xiao-Hui Shanghai Aircraft Design and Research Institute Shanghai China

The safety design of uncontained engine rotor failure for civil aircraft primary flight control systems is more difficult than other airborne systems. This paper presents a safety design method that establishes a two-stage collision model inspection mechanism and introduces an automatic analysis algorithm in the process of comprehensive impact analysis of the cascade system. The method applies to the detailed design stage of civil aircraft systems. It can reduce the difficulty of the safety analysis process and improve the accuracy of the analysis results. The verification of a civil aircraft primary flight control system design shows that after using the safety design method, the time cost of the analysis process is significantly reduced, and the analysis results are more accurate, thereby reducing the difficulty of design changes. © Published under licence by IOP Publishing Ltd.

关键词： Flight control systems

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Assessment of Depression Level Based on Multi-Scale 3D Convolution and Expression Videos 3

Assessment of Depression Level Based on Multi-Scale 3D Convo...

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3rd international conference on Computer Vision and Pattern Analysis, ICCPA 2023

作者： Cao, Qishuang Gao, Junlong Lv, Zeying Li, Mi Department of Automation Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing100124 China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing100124 China Engineering Research Center of Digital Community Ministry of Education Beijing100124 China

ISBN: (纸本)9781510667563

The automatic diagnosis of depression using deep learning has recently shown significant progress, and 3DCNN has been applied to assessing depression levels from videos. There are two problems to be encountered applying 3DCNN, including insufficient data to train the model and an insufficient diversity of features extracted on a single scale. An approach is presented in this paper to address these issues. Firstly, we augmented the raw data by adding noise and applying rotations to increase the amount of the training set. Secondly, we constructed a 3DCNN to extract more diverse features from multiscales. We evaluated our proposed method on the AVEC 2014. Our approach achieved MAE=7.13 and RMSE=9.16, demonstrating its effectiveness in improving the accuracy of depression assessment compared to existing approaches. © 2023 SPIE.

关键词： Deep learning

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Interleaved Boost Converter control Technique Improvements for Fuel Cell Electric Vehicles 1

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3rd international conference on Electronic engineering and Renewable Energy, ICEERE 2022

作者： Benzaouia, Soufyane M’Sirdi, Nacer Rabhi, Abdelhamid Oubbati, Brahim Khalil Zouggar, Smail LIS UMR CNRS 7020 of Aix Marseille University Marseille France Laboratory of Modelisation Information and Systems—MIS UPJV Amiens France LTSS Laboratory Laghouat University Laghouat Algeria Laboratory of Electrical Engineering and Maintenance—LEEM University Mohammed 1st High School of Technology Oujda Oujda Morocco

ISBN: (数字)9789811962233

ISBN: (纸本)9789811962226

This study presents some control technique improvements for an interleaved boost converter for fuel cell electric vehicles. Self-tuning PI controller and an adaptive PI controller using fuzzy logic technique have been designed and developed to improve the voltage tracking accuracy. Several scenarios and tests including load disturbances were carried out to evaluate and to compare the performance of the improved controllers with the conventional one. The obtained results show a superior and high performance of the improved techniques compared to the fixed gains PI controller without adding any extra sensors. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fuzzy logic

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Tuning of subspace predictive controls 3

Tuning of subspace predictive controls

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3rd Modeling, Estimation and control conference (MECC)

作者： Breschi, V. Hamdan, T. Bou Mercere, G. Formentin, S. Eindhoven Univ Technol Dept Elect Engn NL-5600 MB Eindhoven Netherlands Univ Poitiers Lab Informat & Automat Syst 40 Ave Recteur Pineau F-86000 Poitiers France Politecn Milan P zza Leonardo da Vinci 32 I-20133 Milan Italy

ISBN: (纸本)9781713872344

Data-driven predictive control has recently gained increasing attention, as it makes it possible to design constrained controls directly from a set of data, without requiring an intermediate identification step. In this paper, we focus on a Subspace Predictive control (SPC) scheme, with the aim of clarifying the sensitivity of the final closed-loop performance to its main hyperparameters, namely the length of the past horizon and the regularization penalties. Moreover, by delving deep into the structural properties of the control problem formulation, we provide a set of guidelines for the choice of such hyperparameters. The effectiveness of the resulting overall tuning strategy is assessed on two benchmark examples.

关键词： Data-driven predictive control Subspace identification Constrained control

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An Experimental Analysis to Measure the Impact of Data Size on Accuracy of Deep Learning Model to Detect and Classify Monkey-Pox Using Skin Lesion Images 3

An Experimental Analysis to Measure the Impact of Data Size ...

引用

3rd international conference on Technological Advancements in Computational Sciences, ICTACS 2023

作者： Kaur, Gurpreet Handa, Disha Jalodia, Vikas Shukla, Anand Kr. University Institute of Computing Chandigarh University India School of Engineering and Technology Noida International University India

ISBN: (纸本)9798350342338

As a zoonotic disease, Monkey pox is caused by an orthodox virus. This is communicable disease and highly contagious. Detection of the virus at the early stage may stop its spread in the large community. Rapid and accurate diagnosis of monkey-pox is important for effective management and control of outbreaks. Deep learning techniques, a sub-branch of AI, are especially fruitful in visual detection research and many researchers have done fruitful effort in this area. In this study, with the help of experiments, we are doing comparative analysis of detection techniques based on size of dataset. The objective behind is to validate the relationship between accuracy and size of the data. In this study, the analysis is based on the relationship of the size of dataset and accuracy of the model. In order to make observations we have used two different sized datasets and observed that the increase of data of dataset size increases the accuracy of the model. © 2023 IEEE.

关键词： classification Deeplearning Detection Machine learning Monkeypox

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Framework for Design and control of Automatic Stone—Glass Separator 1

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3rd Biennial international conference on Future Learning Aspects of Mechanical engineering, FLAME 2022

作者： Srivastava, Priyank Siddharth Vipul Anmol Shivam Amartya Sharma, Sanjeev Kumar Amity University Noida India

ISBN: (数字)9789819930333

ISBN: (纸本)9789819930326

Nowadays, the technology that has been into the industry revolves around the use of sensors and motors to segregate the waste that is put into the machine/bins. Machine automatically senses the type of waste being put into it and it segregates and pushes down the waste into the respective bin, but these machines have been built on an industrial scale which uses massive conveyer belts and more advanced technology to sense the type of the waste, and these machines are quick but very expensive. The automation in these machines is of utmost importance, and different controls are required for temperature management, operation, and other specific variable control. The present work is the effort of making a scalable model of stone and gas segregator machine. The objective is to segregate glass with similar materials having similar properties. In this study, a framework is proposed for designing and controlling the various sensors that will be used in machine. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Belt conveyors

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Blockchain-Based Ciphertext Access control for Data Sharing 3

Blockchain-Based Ciphertext Access Control for Data Sharing

引用

3rd international conference on Signal Image Processing and Communication, ICSIPC 2023

作者： Wu, Wenli Zhao, Jinyi Chen, Taowei Yu, Yimin School of Information Yunnan University of Finance and Economics Kunming650221 China School of Logistics and Management Engineering Kunming650221 China Intelligent Application Research Institute Yunnan University of Finance and Economics Kunming650221 China

ISBN: (纸本)9781510670945

Currently, with the continuous in-depth research and application of blockchain access control, security issues on the blockchain have become a focus of attention. Based on CPABE, this paper proposes a trusted and secure blockchain access control scheme based on ciphertext policy. Firstly, a decentralized attribute-based encryption algorithm (DABE) is adopted to achieve distributed calculation of user attribute private keys, effectively solving the problems of high trust cost and single point of failure caused by the key center generating private keys in traditional CPABE. At the same time, a private key consensus verification protocol based on zero-knowledge proof is designed to ensure the correctness and security of user attribute private keys without leaking private key information. Through the analysis of on-chain security and experimental simulation, the results show that this scheme has better performance while maintaining high security and is more suitable for distributed access control with large attribute scales. © 2023 SPIE.

关键词： Access control

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Robotic Manipulators: A control Architecture Approach Based on Deep Reinforcement Learning and Simulation Environments

Robotic Manipulators: A Control Architecture Approach Based ...

引用

Electrical, Computer, Communications and Mechatronics engineering (ICECCME), international conference on

作者： Carlos Calderon-Cordova Roger Sarango Dept. of Computer Science and Electronics Universidad Tecnica Particular de Loja Loja Ecuador

With the rapid technological advancement and the increasing need for more intelligent robotic systems in various work areas, it is essential that such systems exhibit improved robustness and control characteristics. In this context, Deep Reinforcement Learning has become a key technique for developing more accurate and efficient control models in robotics. Deep Reinforcement Learning involves training models from a simulated environment that allow different scenarios to be explored without the limitations and constraints of the real world. This allows robotics engineers and developers to fine-tune and improve the control systems of robotic manipulators, making them more reliable and effective in their work. In this article, we present an overview of the main tools, algorithms and simulators used for end-to-end control of robotic manipulators. The use of simulators and Deep Reinforcement Learning techniques in robotic manipulator training allows developers to train robots safely and effectively, without having to deal with the costs and risks associated with training robots in real environments. In addition, concrete examples and applications are included that illustrate how these techniques can be applied to improve the performance and efficiency of robotic manipulator control.

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Humanoid Robots that Move on Two Feet and Are Led by Vision Systems 3

Humanoid Robots that Move on Two Feet and Are Led by Vision ...

引用

3rd international conference on Technological Advancements in Computational Sciences, ICTACS 2023

作者： Singh, Kamred Udham Kumar, Ankit Kumar, Gaurav Singh, Teekam Kumar, Santosh Yadav, Satya Prakash School of Computing Graphic Era Hill University Dehradun India Gla University Department of Computer Engineering & Applications UP Mathura India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Jaipuria Institute of Management Department of Management Jaipur302033 India Glbitm Department of Computer Science and Engineering UP Greater Noida India

ISBN: (纸本)9798350342338

At the convergence of robotics and computer vision lies a crucial research field that focuses on the development of vision-guided walking for humanoid robots. The ability of humanoid robots to walk independently while simultaneously seeing and comprehending their surroundings via the use of visual inputs offers tremendous potential. Humanoid robots are developed to reproduce human-like qualities and skills. This abstract discusses current developments in the area of vision-guided walking for humanoid robots as well as the approaches that have been used. Through the use of computer vision methods in conjunction with walking algorithms, humanoid robots are given the capacity to traverse situations that are both complex and dynamic while exhibiting increased flexibility. For this, real-time sensing of the environment, object identification and avoidance of obstacles, as well as analysis of the terrain, are required in order to arrive at intelligent judgements while moving. Vision-guided walking not only makes robotic locomotion more secure and effective, but it also paves the way for a wide range of potential applications, including exploration, human-robot interaction, search and rescue, and many more. Visual sensing systems, sensor fusion procedures, gait generation methods, motion planning, and control strategies. These topics are discussed in relation to vision-guided walking. Different types of sensors, such as cameras, depth sensors, and LiDAR, are being investigated to see how they can best provide a holistic understanding of the surrounding environment. In addition, the abstract draws attention to the difficulties caused by sensor noise, occlusions, fluctuations in illumination, and the need for real-time processing. In places an emphasis on the role that methods of machine learning play in the improvement of vision-guided walking. The use of deep learning algorithms gives robots the ability to learn from data, hence enhancing their capacity to understand and r

关键词： Head movement in robot Humanoid robots Planning and control Proprioceptive sensors Sensors Vision guided

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Nonlinear control of a Three-Phase, Double-Stage Grid-Tied Photovoltaic System 1

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3rd international conference on Electronic engineering and Renewable Energy, ICEERE 2022

作者： Naddami, Salwa Ababssi, Najib Mokhlis, Mohcine IMII Laboratory Faculty of Science and Technology Hassan First University Settat26000 Morocco Department of Electrical Engineering Mohammadia School of Engineers Mohammed V University Rabat Morocco

ISBN: (数字)9789811962233

ISBN: (纸本)9789811962226

In this paper, a robust backstepping control technique is proposed to enhance the power quality of a double-stage, three-phase grid-connected photovoltaic (PV) system. A two-step control process is used in the research. On the PV array side, P&O-backstepping MPPT is employed to extract the maximum power by controlling a boost DC converter. On the grid side, the backstepping controller is designed to ensure a quasi-total transmission of the extracted PV power to the grid with a unity power factor and reduced harmonic distortion by controlling the d- and q-axis grid currents. The DC link voltage is regulated to maintain a constant value under various conditions, which is employed to obtain a reference value of the direct current vector, that is responsible for active power control. The performance of the backstepping controller in terms of robustness under different operating conditions and disturbances is validated in the MATLAB/Simulink environment. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Maximum power point trackers

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