The four-switch Buck-Boost (FSBB) converter is one of the most popular candidates in various applications. With the quadrangle control strategy, zero-voltage-switching (ZVS) of all power switches can be realized to ac...
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Robust localization, which is the accurate measurement of the position of a user or device in the presence of obstructions or challenging environments, is a fundamental building block for numerous applications. The st...
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ISBN:
(纸本)9798350380903;9798350380910
Robust localization, which is the accurate measurement of the position of a user or device in the presence of obstructions or challenging environments, is a fundamental building block for numerous applications. The standard positioning methods and technologies do not provide satisfactory measurement accuracy in such challenging environments. Therefore, in this paper, a robust localization method is investigated and characterized experimentally. The robust method is capable of estimating the position of a mobile node based on distance measurements with respect to known-position anchors. The method is characterized by means of experiments using the ultra wide band ranging technology. Experimental results in a non line of sight (NLOS) scenario show that the robust localization method may reduce the error by a factor of 4 with respect to the standard method, i.e. the nonlinear least squares. In fact, the robust method results in a median error of approximately 5 cm, whereas the standard method results in a median positioning error of approximately 20 cm.
The integration of distributed power sources into modern power grids has introduced significant network security challenges to Distributed Power Dispatch control Systems (DPDCS). These systems are critical for managin...
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Multi-port dc-dc converters find significance in applications such as renewable integration, and hybrid- source systems. Power flow control and its management is one of the major challenges associated with multi-port ...
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ISBN:
(纸本)9798350370577
Multi-port dc-dc converters find significance in applications such as renewable integration, and hybrid- source systems. Power flow control and its management is one of the major challenges associated with multi-port converters. This work proposes a hybrid model predictive controller for control of power within the integrated dual dc boost converter topology. This topology is a three-port converter with one bidirectional port (suitable for an energy buffer, eg. battery). Due to sharing of control duty ratio using the same set of controllable switches, using separate controllers for each control objective results in cross-regulation within the different ports. This work presents the model predictive controller which can simplify control design for the multi-port system and hence provide robustness to the regulated system. The design of the controller and its evaluation is presented in this work.
Dynamic wireless power transfer systems will have a DC bus, which supplies power to inverters with transmission coils intermittently placed over long distances on the road surface. As the length of the DC bus increase...
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Command and control (C2) agents are a critical component of many cyberattacks, enabling adversaries to maintain covert control over compromised systems. In recent years, attackers have increasingly leveraged real-worl...
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Modular robots offer promising applications in fields like swarm robotics and exploration, and have been extensively explored in the academic research. Specifically, some soft robots, even with the complex system dyna...
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ISBN:
(纸本)9798350395976;9798350395969
Modular robots offer promising applications in fields like swarm robotics and exploration, and have been extensively explored in the academic research. Specifically, some soft robots, even with the complex system dynamics, exhibit their usefulness in tasks involving navigation of unfamiliar environments. In this study, we present a compliant robot design and analyze two-dimensional motion with simulation using various reference trajectories. Subsequently, we validate the optimized simulation parameters on physical hardware, revealing promising potential for effective robot control.
This paper presents a deep learning-based multilayer perceptron (MLP) neural network approach for the design and optimization of electromagnetic absorbers operating in the 20-30 GHz frequency range. This method offers...
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With ongoing advancements in science and technology, artificial intelligence (AI) has emerged as a key driver within modern intelligent logistics. Presently, AI-enabled smart logistics facilitates automated processes ...
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Industry 4.0 is the ongoing automation of conventional manufacturing and industrial applications using smart technology. Quality control (QC) is a set of procedures to ensure that a manufactured product adheres to a d...
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ISBN:
(纸本)9781665439947
Industry 4.0 is the ongoing automation of conventional manufacturing and industrial applications using smart technology. Quality control (QC) is a set of procedures to ensure that a manufactured product adheres to a defined set of quality criteria or meets the requirements of the customer. Many applications within the manufacturing domain employ image-processing or machine learning systems but deep learning-based applications are rare. The goal of this project is to leverage deep learning methods for the automation of quality control. A visual QC automation application is proposed that utilizes a camera placed over a product assembly line containing 3-D printed product samples in a smart factory prototype setup for data collection. After model training, the model will perform object detection and recognition for analyzing complex free-form products and perform product dimension and surface analysis to identify the products that meet the quality control guidelines.
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