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检索条件"任意字段=IEEE Conference on Control Technology and Applications"

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Mixed-Precision Data Driven control of a Complex Dynamic System Model 4

Mixed-Precision Data Driven Control of a Complex Dynamic Sys...

引用

4th ieee Interdisciplinary conference on Electrics and Computer (INTCEC)

作者： Hixenbaugh, Christopher Heryudono, Alfa Chabot, Eugene UMass Dartmouth Comp & Informat Sci N Dartmouth MA 02747 USA UMass Dartmouth Math N Dartmouth MA USA Univ Rhode Isl Elect Comp & Biomed Engn Kingston RI 02881 USA

ISBN: (纸本)9798350349467;9798350349450

Deep Reinforcement Learning (RL) applied to data-driven control exhibits promising outcomes for control tasks with continuous action spaces. A notable drawback of Deep RL lies in its computational demands, which pose a concern when considering deploying Deep RL applications on resource-constrained unmanned platforms. Research in mixed numerical precision methods is actively contributing to enhancing the computational efficiency of Deep Learning approaches. While mixed-precision strategies are established for supervised learning tasks, exploration of this realm is limited for Deep RL. Our objective is to bridge this gap in research by enhancing the computational efficiency of the Deep Deterministic Policy Gradient (DDPG) algorithm through the utilization of mixed-precision and loss scaling. We will present numerical cases to quantify the performance and computational advancements of DDPG agents trained with mixed precision in the context of control for a complex dynamic system model.

关键词： Deep Reinforcement Learning Data-Driven control Autonomous Systems Mixed-Precision Training

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An Algorithm for Cooperative Navigation Using Neural Network to Identify Colored Noise Online

An Algorithm for Cooperative Navigation Using Neural Network...

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2024 ieee International conference on Unmanned Systems, ICUS 2024

作者： Sheng, Danting Cheng, Jin Li, Fengyi Hao, Mingrui Beijing Electro-mechanical Engineering Institute CASIC Beijing China HIWING Technology Academy of CASIC CASIC Beijing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation CASIC Beijing China

ISBN: (纸本)9798350384185

In practical applications of cooperative navigation algorithms based on Kalman filtering, noise is often colored noise, which does not meet the requirement of Gaussian white noise for Kalman ***, an algorithm is proposed to identify and compensate for colored noise online using a BP neural ***, a cooperative navigation model based on Kalman filtering is ***, by studying the update process of Kalman filtering, the neural network is incorporated into the prediction calculation of the observations, following the online learning and updating of the Kalman *** simulations show that under conditions of colored noise, the results of the Kalman filter ***, after correction by the BP neural network, the filtering converges, providing high reference value for improving the accuracy of cooperative navigation. © 2024 ieee.

关键词： Wiener filtering

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IoT applications in Cold Chain Management for Pharmaceuticals: Ensuring Product Integrity and Safety 5

IoT Applications in Cold Chain Management for Pharmaceutical...

引用

5th ieee International conference on Recent Trends in Computer Science and technology, ICRTCST 2024

作者： Panigrahi, Bhawani Sankar Vanitha, A. Palav, Manesh R. Tilak Babu, S.B.G. Nair, Amrutha Muralidharan Bogiri, Nagaraju Vardhaman College of Engineering Department of IT Telangana Hyderabad India Saveetha Engineering College Department of Management Studies Chennai India Dr. D. Y. Patil Vidyapeeth Global Business School & Research Centre Department of MBA Maharashtra Pune India Aditya Engineering College Department of ECE Surampalem India Adi Shankara Institute of Engineering and Technology Department of CSE AI Kerala Ernakulam India Vishwakarma Institute of Information Technology Department of Computer Engineering Maharastra Pune India

ISBN: (纸本)9798350351378

The Cold Chain refers to the process of transporting and storing temperature-sensitive products within a specified temperature range, ensuring that these products maintain their efficacy and safety from manufacturing to end-users. This research explores the various IoT applications that contribute to the optimization of cold chain management, specifically focusing on pharmaceuticals. IoT-enabled devices, sensors, and data analytics play a pivotal role in real-time monitoring, control, and management of temperature-sensitive pharmaceuticals during their entire journey through the supply chain. In conclusion, the adoption of IoT applications in cold chain management for pharmaceuticals represents a paradigm shift in ensuring product integrity and safety. The real-time monitoring, predictive analytics, and enhanced visibility provided by IoT contribute to the overall efficiency of the pharmaceutical supply chain, ultimately safeguarding the well-being of patients and upholding the industry's commitment to delivering high-quality healthcare products. © 2024 ieee.

关键词： Internet of things

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Performance Analysis of Reconfigurable Inverter Battery Systems for Aircraft applications 24

Performance Analysis of Reconfigurable Inverter Battery Syst...

引用

24th International Scientific conference on Electric Power Engineering (EPE)

作者： Sorokina, Nina Bliemetsrieder, Wolfgang Estaller, Julian Karnehm, Dominic Weyh, Thomas Kuder, Manuel Univ Bundeswehr Munich El Power Generat & Distribut Neubiberg Germany Univ Bundeswehr Munich Distributed Intelligent Syst Neubiberg Germany Bavertis GmbH Munich Germany

ISBN: (纸本)9798350348774;9798350348781

The proliferation of electric vehicles for both passenger and cargo transportation in all aspects of life has resulted in the extensive utilization and investigation of various types of electrical power converters, with the aim of identifying the most optimal ones for specific applications based on parameters such as cost, complexity of control algorithms, power losses, reliability and many others. This paper evaluates the performance of three battery pack multilevel inverter topologies for aircraft applications using simulation results. The topologies under consideration are the Cross-Switched, Cascaded Half-Bridges, and Battery Modular Multilevel Management Converter. All three topologies enable the integration of the DC-AC converter, Battery Management System, and onboard charger functions on a single platform.

关键词： inverter MOSFET multilevel light aircraft battery cells losses

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RF Classification of UAVs Using MLP Model and Software Defined Radio 21

RF Classification of UAVs Using MLP Model and Software Defin...

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2024 ieee/ACS 21st International conference on Computer Systems and applications, AICCSA 2024

作者： Montassar, Abdenneji Delleji, Tijeni Slimeni, Feten Abid, Mohamed Ali Attia, Rabah The Military Academy of Fondouk Djedid Telecommunication Department Nabeul Tunisia Military Research Center Science and Technology for Defense Lab Aouina Tunisia Tunisia Polytechnic School Lab of Electronic Systems and Communications Networks Marsa Tunisia

ISBN: (纸本)9798331518240

The use of commercial off-the-shelf (COTS) drones has been exponential growth, whether for leisure or professional purposes. In addition to the beneficial applications, they recently raised security threats for critical and strategic sites such as nuclear power plants, airports, and stadiums. Therefore, the need to detect these targets becomes essential for national security. The chosen approach is based on the detection of the RF signal related to the remote control (RC) link of the drone system using software-defined radio (SDR). The RF fingerprints are then extracted, we have considered the standard deviation (std), kurtosis, skewness, and Peak-to-Average Power Ratio (PAPR). These features and used for classification based on a customized Multi layer perceptron (MLP) model to identify the detected target. © 2024 ieee.

关键词： Drones

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A Fuel-Cell Driven Brushless-Direct Current Electric Motor Drive for Green Transport applications 3

A Fuel-Cell Driven Brushless-Direct Current Electric Motor D...

引用

3rd ieee International conference on Electrical Power and Energy Systems, ICEPES 2024

作者： Shukla, Tanmay Ansari, Aftab Ahmed Mishra, Neelam Ansari, Anwar Ahamed Patidar, N.P. Barode, Shyam Kumar Maulana Azad National Institute of Technology Department of Electrical Engineering Bhopal India Bansal Institue of Research and Technology Electrical & Electronics Engineering Department Bhopal India

ISBN: (纸本)9798350390728

Over the last several decades, fuel cells, or FCs, have garnered a lot of attention in the automobile sector due to their simplicity of use, quiet operation, exceptional performance, and modular architecture. In this article, a solid oxide fuel cell (SO-FC) powered brushless DC electric motor (BLDCEM) drive is presented for green transport applications. The BLDCEM drive model uses a Cuk converter in between SO-FC and voltage source inverter (VSI) -fed BLDCEM. The discontinuous inductor current (DIC) mode control is used in this work to maintain constant DC-link voltage. The discontinuous operation not only reduces the size of the converter's elements but also reduces the sensor requirements which lowers the system cost. The electronic commutation scheme is used to generate the gate pulse for VSI because of which the losses associated with moving elements are eradicated. The complete system is built on the MATLAB platform and results are discussed in detail. © 2024 ieee.

关键词： Solid oxide fuel cells (SOFC)

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Smart Intelligent control Application Using Quantum Computation and Machine Learning 2

Smart Intelligent Control Application Using Quantum Computat...

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2nd ieee International conference on IoT, Communication and Automation technology, ICICAT 2024

作者： Singh, Amit Ranjan, Roop Kapil, Alok Govil, Ravi Raghav, Prabhat Institute of Technology & Science Department of Computer Application Ghaziabad India Budhha Institute of Technolgy Department of Computer Science & Engg. Gorakhpur India Deptt. of Computer Science & Engg. Ghaziabad India

ISBN: (纸本)9798350368109

Machine learning (ML) is significantly transforming and modernizing urban areas by enhancing service quality across various sectors such as transportation, security, robotics, healthcare, energy, and finance."Even with their overwhelming success, machine learning (ML) algorithms still require significant computational work with fast computer hardware in order to handle model complexity and guarantees that result in effective, dependable, and robust solutions. Regarding cyber security and digital protection, quantum computing (QC) is a formidable contender to assist machine learning (ML) systems achieve optimal performance. "This research aims to develop the Quantum Adaptive Neuro-Fuzzy Inference System (QANFIS) model for detecting distributed denial of service attacks in smart control applications. The usefulness of our proposed model is demonstrated by evaluating it against an actual dataset of denial of service attack incidents. Lastly, various unresolved problems and difficulties with fitting ML with QC are discussed along with the findings. © 2024 ieee.

关键词： Adversarial machine learning

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Adaptive Fuzzy Secure Consensus control of Nonlinear Multi-Agent Systems Under Deception Attacks

Adaptive Fuzzy Secure Consensus Control of Nonlinear Multi-A...

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2024 International conference on Fuzzy Theory and Its applications, iFUZZY 2024

作者： Bi, Yannan Ding, Pansheng Wang, Fei Wang, Tong Qiu, Jianbin Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin150001 China

ISBN: (纸本)9798350352788

This paper investigates the secure consensus control problem for nonlinear multi-agent systems (MASs) under de-ception attacks. The main characteristic of the proposed secure consensus control method is its ability to mitigate undesirable system behaviors caused by deception attacks at the communication links among different agents. In particular, the relationship between the compromised signals and the output signals of MASs is analyzed. Furthermore, a novel Nussbaum function and an adaptive fuzzy law are respectively proposed to tackle the unknown control direction and to estimate the unknown terms caused by deception attacks. Simulation results are presented to demonstrate the validity of the proposed adaptive consensus secure control method. © 2024 ieee.

关键词： Multi agent systems

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Analysis of Serial Peripheral Interface 2

Analysis of Serial Peripheral Interface

引用

2nd ieee International conference on Measurement, Instrumentation, control and Automation, ICMICA 2023

作者： Patra, Aritra Saini, Lalit Mohan National Institute of Technology School of Vlsi and Embedded System Design Haryana Kurukshetra India National Institute of Technology Department of Electrical Engineering Haryana Kurukshetra India

ISBN: (纸本)9798350355048

Serial peripheral interface, a term originally coined by Motorola in the 1980s, serves as a protocol facilitating the communication of serial synchronous data between a master device, often a microcontroller, and various peripherals. These peripherals encompass a broad range, including EEPROMs (Electrically Erasable Programmable Read-Only Memory), sensors, cards and more. Functioning as a full-duplex serial protocol, SPI (Serial peripheral interface) involves transmission and reception of synchronous serial data. This document elucidates the operational intricacies and distinctive features of the SPI Interface Protocol, focusing on a configuration with one master and one slave. In this setup, master device orchestrates communication, dictating the timing and flow of data, while slave device responds to master's commands. Understanding working principles and characteristics of SPI is paramount for its effective implementation in diverse applications. © 2024 ieee.

关键词： Mice (computer peripherals)

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Application of the YOLOv8 Model to a Fruit Picking Robot 2

Application of the YOLOv8 Model to a Fruit Picking Robot

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2nd ieee International conference on control, Electronics and Computer technology, ICCECT 2024

作者： Gu, Yicheng Hong, Ruicong Cao, Yonghu East China University of Science and Technology Shanghai China

ISBN: (纸本)9798350380958

Due to the current labor shortage in fruit picking, the utilization of robots for harvesting has become crucial in addressing this issue. This paper presents two key models, an apple image recognition model and an apple image recognition classification model, both based on Yolov8. These models are specifically designed and trained to be implemented in apple picking robots. In Model1, the RGB color space was chosen, and the image data underwent preprocessing using Gaussian filtering. The training process utilized manually labeled data. Model 2, on the other hand, involved data grouping and training using the Yolov8 model, with a focus on optimizing the recognition results. The feasibility of these models was rigorously tested through extensive modeling experiments. This research not only offers a solution for the labor shortage in fruit picking robots but also demonstrates its wide-ranging potential in real-life applications and sales processes. Furthermore, the insights gained from this study can contribute to the advancement of automatic recognition and classification of other fruits, thereby fostering the intelligent development of fruit picking robots. © 2024 ieee.

关键词： Fruits

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