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European Conference on Antennas and Propagation, EuCAP

作者： Natasha Birari Yanki Aslan Alexander Yarovoy Department of Microelectronics Faculty of Electrical Engineering Mathematics and Computer Science Microwave Sensing Signals and Systems Group Delft University of Technology Delft The Netherlands

An improved system-level power consumption model (PCM) for 5G base station multi-beam phased-array transmit architectures is developed. Using this model, it is shown that an optimum number of antenna elements of the array exists with respect to the total power consumption. The proposed model is benchmarked against a recent study which is shown to underestimate the total power consumed in analog and digital antenna systems by 37% and 126% respectively.

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A Machine Learning Approach for High Resolution Fractional Vegetation Cover Estimation Using Planet Cubesat and RGB Drone Data Fusion

A Machine Learning Approach for High Resolution Fractional V...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Jacob Nesslage Brittany Lopez Barreto Adam Weingram Erin Hestir Environmental Systems Graduate Group University of California Merced Department of Civil and Environmental Engineering University of California Merced Department of Electrical Engineering and Computer Science University of California Merced

High resolution fractional vegetation cover (HR-FVC) is important for many applications, including precision agriculture, forestry, and conservation. For land managers, HR-FVC is most useful when the data can be produced quickly with minimal effort. In this study, we perform data fusion of RGB drone data and multispectral cubesat data for synthetic daily HR-FVC estimation. First, binary classification of 10cm resolution drone data was used to identify vegetation. An AdaBoost model (Accuracy = 0.868, F1-score = 0.840) was selected for further analysis. HR-FVC training data was then produced from drone vegetation maps by calculating the FVC in a 3m pixel – Planet SuperDove resolution, resulting in 238,270 training points. A random forest regression model was used to predict HR-FVC from Planet SuperDove data. The final model’s performance is comparable to similar studies (R 2 = 0.720, RMSE = 0.213), suggesting the methodology could be viable for applications requiring daily HR-FVC datasets.

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Shaped-Beam Subarrays for Equi-Power Urban Area Coverage With Modularity and Low Cost

Shaped-Beam Subarrays for Equi-Power Urban Area Coverage Wit...

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European Conference on Antennas and Propagation, EuCAP

作者： Changxu Zhao Alexander Yarovoy Antoine Roederer Yanki Aslan Department of Microelectronics Aculty of Electrical Engineering Mathematics and Computer Science Microwave Sensing Signals and Systems Group Delft University of Technology Delft The Netherlands

Design of millimeter-wave arrays for base stations operating in dense urban environment is investigated. Innovative designs for linear subarrays with shaped beam patterns for hybrid beamforming are proposed. The number of elements and element spacings in the subarrays are optimally selected based on a pattern matching technique. The subarrays are designed and verified in series edge-fed slotted substrate integrated waveguide technology at 26 GHz. A novel phase shifter unit is proposed to reduce the subarray width for grating lobe-free beam steering in the plane orthogonal to the sub-array axis. Infinite array simulations are performed to observe the coupling effects on the subarrays.

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Efficient Embedded Element Pattern Prediction via Machine Learning: A Case Study with Planar Non-Uniform Sub-Arrays

Efficient Embedded Element Pattern Prediction via Machine Le...

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European Conference on Antennas and Propagation, EuCAP

作者： Nehir Berk Onat Ignacio Roldan Francesco Fioranelli Alexander Yarovoy Yanki Aslan Department of Microelectronics Faculty of Electrical Engineering Mathematics and Computer Science Microwave Sensing Signals and Systems Group Delft University of Technology Delft The Netherlands

Efficient prediction of embedded element patterns (EEPs) is including the mutual coupling (MC) effects in the optimization of irregular planar arrays is studied for the first time in the literature. An ANN-based methodology is used to predict the pattern of each element in the whole visible space for a flexible planar array topology in milliseconds. The technique is proposed is validated on a 4-element planar non-uniform sub-array structure. Excellent accuracy on the EEP prediction while providing great efficiency in computational time and load in comparison to the full-wave simulations is demonstrated.

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Low Complexity Single-Snapshot DoA Estimation via Bayesian Compressive Sensing

Low Complexity Single-Snapshot DoA Estimation via Bayesian C...

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IEEE National Conference on Radar

作者： Ignacio Roldan Lucas Lamberti Francesco Fioranelli Alexander Yarovoy Department of Microelectronics Microwave Sensing Signals and Systems Group Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft The Netherlands

The problem of single-snapshot direction of arrival (DoA) estimation with antenna arrays has been considered. A sectorized approach based on Bayesian Compressive Sensing (BCS) has been proposed. In this method, the angular space is discretized, defining many non-overlapping small grids which cover the desired large angular space. First, a BCS estimation is run in each of the sectors to estimate the DoA of the signals. Then, a second stage is performed to correct the inconsistencies at the edges due to signal leaking between sectors. The performance of the method has been analyzed via extensive Monte-Carlo simulations in which the number of targets, their Radar Cross Section (RCS), and their location have been varied in a large extent, and the targets were observed by a Frequency Modulated Continuous Wave (FMCW) radar with an 86-element Uniform Linear Array (ULA). The results are compared with state-of-the-art methods in terms of estimation accuracy and resolution. Moreover, an analysis of the computational time, critical for many real-time applications, is presented, which shows a reduction of 20 times in the computational time compared with the standard BCS. Finally, the method has also been validated using experimental data collected with a commercial automotive radar.

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Statistical Effects of Propagation Environment and Transmit Array Topology on Cell-Edge User Service Quality at mm-Waves

Statistical Effects of Propagation Environment and Transmit ...

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European Conference on Antennas and Propagation, EuCAP

作者： Nicolas Van De Kreeke Yanki Aslan Nehir Berk Onat Alexander Yarovoy Department of Microelectronics Microwave Sensing Signals and Systems Group Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft The Netherlands

The effects of multipath on the statistical cell-edge user service quality is for the first time investigated for mm-wave multi-user communication systems. The focus is given on setting the user spacing constraints and the transmit array topology via thinning, which can be used to enhance wireless security or decrease analog/digital complexity. A hybrid line-of-sight/non-line-of-sight channel is created by using a statistical model following the communication standards. The multipath signal components are included in the model by using non-coherent or coherent modes of operation. It is shown in simulation that selection, by the medium access control layer, of large angular spacings between the simultaneously served users and application of antenna array thinning at the array edges improves the system performance.

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A Novel Heatsink Attached mm-Wave Active Patch Antenna With Adjustable Frequency and Cooling

A Novel Heatsink Attached mm-Wave Active Patch Antenna With ...

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European Conference on Antennas and Propagation, EuCAP

作者： Feza Turgay Celik Yanki Aslan Department of Microelectronics Faculty of Electrical Engineering Mathematics and Computer Science Microwave Sensing Signals and Systems Group Delft University of Technology Delft The Netherlands

In this study, the thermal management problem of the modern communication systems with small array sizes is addressed. A novel dual-functional active antenna design strategy is introduced for adjustable frequency of operation and cooling extension at millimeter-wave bands. The concept is based on placing different types of heatsinks on the same patch antenna. The electromagnetic and thermal behavior of the proposed heatsink structures are presented via simulations. Reconfigurable operation at 24, 26, and 28 GHz frequencies with 23 to 28 degrees of extra cooling in the chip as compared to the conventional patch is achieved.

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Distributed consensus-based voltage and frequency control for isolated microgrids with fault-induced delayed voltage recovery mitigation

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Frontiers in Energy Research 2024年 12卷

作者： Alghamdi, Baheej Smart Grids Research Group Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz University Jeddah Saudi Arabia Department of Electrical and Computer Engineering King Abdulaziz University Jeddah Saudi Arabia

This paper presents a distributed consensus-based voltage and frequency control (VFC) strategy for isolated microgrids with distributed energy resources (DERs) and induction motor loads. The proposed controller coordinates the DERs to regulate microgrid frequency and voltage while mitigating fault-induced delayed voltage recovery (FIDVR), a phenomenon where system voltage remains depressed for several seconds after fault clearance due to induction motor stalling. The VFC loop adjusts DER voltage setpoints based on frequency deviation and voltage level to regulate voltage and mitigate FIDVR events, while the active power control loop maintains frequency stability by coordinating active power sharing among DERs and compensating for the constant power load behavior of stalled induction motors. A proximity-based reactive power support prioritization and a distributed voltage estimator enhance the controller’s response to FIDVR events. Coordination between the VFC and active power control loops is achieved through adaptive gain adjustment and a voltage recovery coordination term. Simulation results demonstrate the effectiveness of the proposed controller in maintaining microgrid stability, ensuring fast voltage recovery, and providing robust performance under various operating conditions, including communication delays and different fault durations. Copyright © 2025 Alghamdi.

关键词： Microgrids

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Learning Reduced-Order Linear Parameter-Varying Models of Nonlinear systems ⁎

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IFAC-PapersOnLine 2024年第15期58卷 265-270页

作者： Patrick J.W. Koelewijn Rajiv Singh Peter Seiler Roland Tóth Sioux Technologies B.V. Eindhoven The Netherlands Control Systems Group Eindhoven University of Technology Eindhoven The Netherlands The MathWorks Inc. Natick USA Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor USA Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Budapest Hungary

In this paper, we consider the learning of a Reduced-Order Linear Parameter-Varying Model (ROLPVM) of a nonlinear dynamical system based on data. This is achieved by a two-step procedure. In the first step, we learn a projection to a lower dimensional state-space. In step two, an LPV model is learned on the reduced-order state-space using a novel, efficient parameterization in terms of neural networks. The improved modeling accuracy of the method compared to an existing method is demonstrated by simulation examples.

关键词： Reduced-order modeling Neural Networks Linear Parameter-Varying Models

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A Data-Driven Distributed Control Scheme: Learning Multi-Objective Agent-Based MPC for Path-Tracking

A Data-Driven Distributed Control Scheme: Learning Multi-Obj...

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International Conference on Intelligent Transportation

作者： Jiaming Zhong Reza Valiollahi Mehrizi Yash Vardhan Pant Amir Khajepour Department of Mechanical and Mechatronics Engineering Mechatronic Vehicle Systems (MVS) Lab University of Waterloo Waterloo ON Canada Department of Electrical and Computer Engineering Control Learning and Logic (CL2) group University of Waterloo Waterloo ON Canada

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

Agent-based model predictive control (AMPC) has recently been proposed for vehicle systems with various controllers, such as differential braking and torque vectoring, where controllers are regarded as distributed agents contributing to the same objective. However, this scheme is challenging in handling multiple conflicting objectives with coupled agents. A common approach for such tasks is the integrated MPC, where all objectives and agents are stacked together in one optimization. Nevertheless, as more agents and objectives are involved, the integrated MPC will face challenges like computational burdens and maintenance difficulties in practice. To this end, this paper proposes a learning multi-objective AMPC that can improve design flexibility and computing efficiency. First, under the assumption of information exchange, a multi-objective AMPC tailored from the alternating direction method of multipliers (ADMM) is proposed to decouple the system and achieve the same performance as the integrated scheme iteratively. Second, a learning-based method for initializing iterations is proposed to accelerate convergence. In addition, a data management method is proposed for real-time efficiency, and an authentication module is designed for learning reliability. We compare the proposed scheme against the integrated scheme via a combined path-tracking simulation for autonomous vehicles with various controllers. The proposed scheme achieves the same control performance as the integrated one while reducing the computational time by 43.5 %. Furthermore, the learning-based method saves 88.6% more computational time than without learning, making it suitable for real-time implementation.

关键词： Learning systems Torque Decentralized control Reliability engineering Real-time systems Convex functions Planning Information exchange Convergence Predictive control

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