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Articles 14491 - 14520 of 198069

Full-Text Articles in Engineering

Spin Mechanisms In Gd-Doped Gan Implanted With Oxygen Carbon At Room Temperature, Vishal Saravade, Amirhossein Ghods, Chuanle Zhou, Ian Ferguson Jan 2025

Spin Mechanisms In Gd-Doped Gan Implanted With Oxygen Carbon At Room Temperature, Vishal Saravade, Amirhossein Ghods, Chuanle Zhou, Ian Ferguson

Electrical and Computer Engineering Faculty Research & Creative Works

Gadolinium-doped gallium nitride implanted with oxygen and carbon show carrier-mediated spin mechanisms at room temperature. As-grown Gd-doped GaN grown by metal-organic chemical vapor deposition using a tris(cyclopentadienyl) gadolinium precursor shows Ordinary Hall Effect and no ferromagnetism at room temperature. Upon O or C implantation in Gd-doped GaN, Anomalous Hall Effect that is indicative of carrier-mediated spin and ferromagnetism is observed. A good crystal quality is maintained even after implantation. O and C favor interstitial sites and occupy deep-level acceptor-type states in Gd-doped GaN. Room-temperature spin and ferromagnetism that is induced by gadolinium in Gd-doped GaN is activated by O and …


Quality Factor Estimation Of Additively Manufactured Frequency Selective Surfaces Via Active Microwave Thermography, Logan M. Wilcox, Alexander Hook, Emma T. Bohannon, Doyle T. Motes, Cody Morrow, Kristen M. Donnell Jan 2025

Quality Factor Estimation Of Additively Manufactured Frequency Selective Surfaces Via Active Microwave Thermography, Logan M. Wilcox, Alexander Hook, Emma T. Bohannon, Doyle T. Motes, Cody Morrow, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Additive manufacturing (AM) has increased in popularity in recent years due to improvements in efficiency over traditional manufacturing methods. Furthermore, the availability of electrically conductive fused deposition modeling (FDM) filaments has opened the door to the manufacture of conductive structures, including frequency selective surfaces (FSSs). Traditionally, the performance of an FSS is verified experimentally through electromagnetic (EM) measurement of the FSS's reflection and/or transmission response. However, this verification approach is not ideal for rapid, in situ inspections due to the time-consuming measurement process, expensive and complicated equipment, and difficult to interpret results. To this end, active microwave thermography (AMT), a …


Multi-Source Remote Sensing–Based Soil Moisture Prediction Using Machine Learning, Niraj Neupane Jan 2025

Multi-Source Remote Sensing–Based Soil Moisture Prediction Using Machine Learning, Niraj Neupane

Electronic Theses and Dissertations

Soil moisture (SM) plays a central role in climatic and environmental processes, influencing shear strength of soil, agricultural productivity, land–atmosphere interactions, and hydrologic functioning. However, accurately estimating SM across diverse climatic regions remains challenging due to spatial heterogeneity, limited in situ measurements, and inconsistencies in sensor resolution. Machine learning (ML) and remote sensing offer promising avenues for improving SM prediction, yet many existing approaches struggle with generalization across climatic gradients and often fail to capture temporal variability. This study integrates multi-source satellite and climate datasets, including SMAP L4_SM, MODIS land surface temperature, Daymet meteorological variables, and in situ observations from …


Quantitative Assessment And Validation Of Thermal Profiles In The Protodune-Ii Horizontal Drift Detector Using Computational Fluid Dynamics, Hunter Wallster Jan 2025

Quantitative Assessment And Validation Of Thermal Profiles In The Protodune-Ii Horizontal Drift Detector Using Computational Fluid Dynamics, Hunter Wallster

Electronic Theses and Dissertations

The Deep Underground Neutrino Experiment (DUNE) aims to advance understanding of neutrino properties using large liquid Argon time projection chambers (LArTPCs). The ProtoDUNE-II Horizontal Drift (HD) detector, constructed at CERN in Switzerland, serves as 1:20 scale prototype to validate design and operational parameters for DUNE’s Far Detectors. Accurate prediction of cryostat thermal behavior is critical to predicting liquid Argon purity distributions and detector performance, motivating the development of a validated computational fluid dynamics (CFD) model. This research extends previous work at South Dakota State University by constructing a higher-fidelity CFD simulation of ProtoDUNE-II HD using Siemens Simcenter StarCCM+® 19.04.007. Geometry …


Mid-Scale Rover Gravity Offloader (Mrgo): Design, Implementation, And Experimental Validation, Alexander Schaar Jan 2025

Mid-Scale Rover Gravity Offloader (Mrgo): Design, Implementation, And Experimental Validation, Alexander Schaar

Electronic Theses and Dissertations

This thesis presents the design, implementation, and validation of the Mid Scale Rover Gravity Offloader (MRGO), a terrestrial testbed developed to simulate partial-gravity conditions for planetary rover testing within a three-dimensional environment. The MRGO enables consistent, user-defined offloading force as a rover drives freely within a 20 by 18 ft test area, while a stepper motor rail gantry autonomously tracks the rover’s motion and maintains overhead alignment. Mounted to the moving gantry is a vertical carriage column that houses the offloading mechanism, which accommodates up to 5 ft of vertical displacement without loss of force accuracy. This configuration allows realistic …


Development Of Bio-Based Coating Materials For Environmentally Friendly Controlled-Release Nitrogen Fertilizer Applications, Anne Carolyne Mendonca Cidreira Jan 2025

Development Of Bio-Based Coating Materials For Environmentally Friendly Controlled-Release Nitrogen Fertilizer Applications, Anne Carolyne Mendonca Cidreira

Electronic Theses and Dissertations

No abstract provided.


Computation-Efficient Deep Learning Models For Computer Vision And Multimodal Vision-Language Tasks Via Network Pruning, Abir Mohammad Hadi Jan 2025

Computation-Efficient Deep Learning Models For Computer Vision And Multimodal Vision-Language Tasks Via Network Pruning, Abir Mohammad Hadi

Electronic Theses and Dissertations

With the rapid evolution of deep neural networks over the past decade, the demand for efficient, generalizable, and task-adaptable models, especially in computer vision, has increased significantly. To address the computational and deployment challenges posed by overparameterized models, the research community has extensively explored model compression techniques such as pruning, quantization, and distillation. These approaches aim to enhance model efficiency without compromising performance, particularly when adapting to domain-specific tasks under limited resources. This dissertation investigates several underexplored yet critical aspects of task-aware deep learning model compression, spanning both convolutional and vision-language architectures. In the early part of this work, we …


Effects Of Peel Angle And Strain Rate On The Bond Between Frcm Composite And Concrete Substrate, Lucas Robert Gervais Jan 2025

Effects Of Peel Angle And Strain Rate On The Bond Between Frcm Composite And Concrete Substrate, Lucas Robert Gervais

Electronic Theses and Dissertations

Fiber-reinforced cementitious matrix (FRCM) composites have gained increasing attention for the rehabilitation and strengthening of concrete and masonry structures due to their favorable mechanical properties, compatibility with existing substrates, and ease of application. The effectiveness of any strengthening procedure depends on the quality of the bond between the external reinforcement and the substrate, ensuring efficient stress transfer and enabling the system to reach its ultimate capacity without premature debonding. While research has focused on the bond performance of FRCM systems under pure shear loading and quasi-static, low strain rate conditions, the effects of mixed-mode loading and high strain rates representative …


Simulating Positive Ion Distribution In The Protodune Single Phase Detector, Vishnu Pfeiffer Jan 2025

Simulating Positive Ion Distribution In The Protodune Single Phase Detector, Vishnu Pfeiffer

Electronic Theses and Dissertations

This work covers the validation and implementation of a model to solve for argon ion (Ar+) distribution in the ProtoDUNE-SP liquid argon time projection chamber (LArTPC). ProtoDUNE-SP undergoes a constant flux of cosmic ray muons due to surface operation. The performance of the ProtoDUNE-SP provided valuable insights into single-phase technology, membrane cryostat technology, and calibration of cryogenic instrumentation. Still, challenges in achieving precise measurements persist due to the space charge effect—the distortion of the electric field within the detector due to the accumulation of positive argon ions generated from constant cosmic muon flux. The overarching goal of this thesis is …


Impact Of Automated Controlled Tile Drainage On Field Discharge Water, Soil Moisture, And Crop Yield In Southeastern South Dakota, Joshua Becker Jan 2025

Impact Of Automated Controlled Tile Drainage On Field Discharge Water, Soil Moisture, And Crop Yield In Southeastern South Dakota, Joshua Becker

Electronic Theses and Dissertations

Automated controlled tile drainage is an innovative approach to water management, using dynamic weir settings programmed to drain water out of the tile system if it encroaches into the root zone at pre-programmed depths and duration. While past studies have indicated potential yield and water quality benefits of controlled drainage, there has been very little research into the performance of automated controlled drainage. In addition to overall performance, there is a gap in knowledge of management settings to optimize yield and water quality benefits. Two experiments, one plot-scale and one modeling, were conducted to assess the impact of automated controlled …


Lunar Payload Logistics: Advancing Autonomous Control For Lunar Surface Transporter Vehicles, Liam Murray Jan 2025

Lunar Payload Logistics: Advancing Autonomous Control For Lunar Surface Transporter Vehicles, Liam Murray

Electronic Theses and Dissertations

No abstract provided.


Evolution Of Bed Shear Stress In Open Channel Flow Over A Rough-To-Smooth Transition, Monika Kafle Jan 2025

Evolution Of Bed Shear Stress In Open Channel Flow Over A Rough-To-Smooth Transition, Monika Kafle

Electronic Theses and Dissertations

The study of flow over roughness transition in an open channel is very important in the field of hydraulic engineering. Bed shear stress is the key factor in predicting sediment transport and determining the stability of hydraulic structures while flow depth, flow velocity, surface roughness are some hydraulic parameters that can affect the bed shear stress in an open channel flow. In this thesis, a detailed investigation into the development of bed shear stress in a rough-to-smooth transition is performed. Experiments were conducted on flow over a rough-to-smooth transition in an open channel flume with an M2 to S2 composite …


Molecular Dynamics Simulations Of Key Parameters On Thermal Properties Of Carbon Nanotube Modified Epoxy Composites, Lida Najmi Jan 2025

Molecular Dynamics Simulations Of Key Parameters On Thermal Properties Of Carbon Nanotube Modified Epoxy Composites, Lida Najmi

Electronic Theses and Dissertations

The application of carbon nanotube (CNT)-reinforced epoxy matrix composites (CRECs) has attracted extensive attention in various industrial sectors due to the significant improvement of material properties imparted by CNTs. The thermal behavior of these nanocomposites is governed by complex heat transfer mechanisms operating at different scales, resulting in a complex relationship between the effective thermal response and the microstructural characteristics of the composite. In this study, molecular dynamics (MD) simulations were used to investigate the thermal conductivity of CRECs, focusing on the effects of key parameters such as the length and volume fraction of CNTs, the degree of cross-linking within …


Measurement- And Simulated Annealing (Sa) Optimization-Based Inductor Model Coupled To Chassis, Junyong Park, Reza Vahdani, Donghyun Kim Jan 2025

Measurement- And Simulated Annealing (Sa) Optimization-Based Inductor Model Coupled To Chassis, Junyong Park, Reza Vahdani, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

In automotive systems, a metal chassis protects the components against the external environment. However, the metal chassis is conductive, which results in unwanted conducted emission (CE) coupling to electric components. An inductor used for power factor correction (PFC) is one of the affected components. When the inductor is mated with the metal chassis, the impedance of the inductor changes. It is also hard to predict the CE coupling due to the structure-dependent characteristics. That is, the CE coupling is not negligible and hard to clarify. Therefore, this article proposes an efficient modeling method for the inductor which is mated with …


Mitigating Optical Module Emi Using Common- And Differential-Mode Filters, Shivali Singh, Rakshith Kumar Gopalaiah, Di Li, Mokshit Tejasvi, Shipra Shipra, Victor Khilkevich Jan 2025

Mitigating Optical Module Emi Using Common- And Differential-Mode Filters, Shivali Singh, Rakshith Kumar Gopalaiah, Di Li, Mokshit Tejasvi, Shipra Shipra, Victor Khilkevich

Electrical and Computer Engineering Faculty Research & Creative Works

A strategy to mitigate electromagnetic interference in quad/octal small form-factor pluggable interfaces using a common-mode/differential-mode filter is presented in this research. Differential source imbalance produces significant common- and differential-mode noise in the differential pseudorandom binary sequence signal. EMI associated with this noise can be reduced by incorporating a band stop filter onto the differential line on a printed circuit board. Two kinds of filters were tested: common mode and common/differential mode. It was demonstrated that the application of a common-mode/differential-mode filter is more advantageous than a common-mode filter and allows to achieve the suppression of the total radiated power by …


Radiated Susceptibility Testing Using Near-Field Scanning, Mckennan Starkey, Aaron Harmon, Cody Goins, Kristen Donnell, Victor Khilkevich, Daryl Beetner Jan 2025

Radiated Susceptibility Testing Using Near-Field Scanning, Mckennan Starkey, Aaron Harmon, Cody Goins, Kristen Donnell, Victor Khilkevich, Daryl Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Determining locations and components in a system responsible for radiated coupling is challenging. Methods, such as near field injection susceptibility scanning or direct power injection, can only find locations and frequencies where a component is sensitive to the near field or to an injected signal but cannot deduce if the component is well coupled to the far-field. In this paper, a method to experimentally determine the levels of radiated coupling within a target system is proposed. A near-field differential loop probe is scanned over the target device while measuring the radiated energy in a stirred-mode tent. By sweeping the near …


Ai-Driven Traffic Scene Understanding Using Static Lidar Sensors, Elham Binshaflout, Chaima Zaghouani, Charalampos Antoniadis, Hakim Ghazzai, Nawfal Guefrachi, Ahmad Alsharoa, Sameh Najeh, Gianluca Setti Jan 2025

Ai-Driven Traffic Scene Understanding Using Static Lidar Sensors, Elham Binshaflout, Chaima Zaghouani, Charalampos Antoniadis, Hakim Ghazzai, Nawfal Guefrachi, Ahmad Alsharoa, Sameh Najeh, Gianluca Setti

Electrical and Computer Engineering Faculty Research & Creative Works

Traffic congestion and road safety remain critical challenges in urban environments, driving the need for more effective traffic monitoring solutions. While recent advancements in computer vision have enhanced traffic perception, the dynamic viewpoint of autonomous vehicles is often insufficient for comprehensive traffic management. To address this gap, we propose an AI-driven framework for enhanced traffic scene understanding using static LiDAR sensors at road intersections. The system collects 3D point clouds from roadside static LiDAR sensors, providing a complete view of vehicles and pedestrians. We integrate state-of-the-art 3D object detection (i.e., PV-RCNN) and instance segmentation models (i.e., PointGroup3heads) to accurately identify …


Differential Via Modeling Using Multilayer Perceptron-Sequential (Mlp-Seq) Neural Network, Hyunwook Park, Shruti Sawant, Bandi Sathvika, Arun Chada, Soumya Singh, Seema Pk, Taein Shin, Haeseok Suh, Junyong Park, Bhyrav Mutnury, Donghyun Kim Jan 2025

Differential Via Modeling Using Multilayer Perceptron-Sequential (Mlp-Seq) Neural Network, Hyunwook Park, Shruti Sawant, Bandi Sathvika, Arun Chada, Soumya Singh, Seema Pk, Taein Shin, Haeseok Suh, Junyong Park, Bhyrav Mutnury, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, an encoder-decoder structured multi-layer perceptron-sequential (MLP-SEQ) networks are proposed to model high-speed differential vias for estimating differential insertion loss (IL) and return loss (RL). Sequential neural networks including recurrent neural network (RNN), long short-term memory (LSTM), and gated recurrent unit (GRU) are introduced as the decoder NN to treat frequency responses as sequences. The proposed models are validated by finite element method (FEM) simulation results. The accuracy and training times of MLP-RNN, MLP-LSTM, and MLP-GRU models are compared and analyzed. Based on the MLP-LSTM model, various design of experiments (DoEs) are conducted to enhance the reproducibility and …


Coupling Path Analysis Of Data Center Ssd Storage Systems Based On Visualization Technique, Xiangrui Su, Haran Manoharan, Jihun Kim, Lalit Kumar, Heewon Kang, Chunghyun Ryu, Chulsoon Hwang Jan 2025

Coupling Path Analysis Of Data Center Ssd Storage Systems Based On Visualization Technique, Xiangrui Su, Haran Manoharan, Jihun Kim, Lalit Kumar, Heewon Kang, Chunghyun Ryu, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

Electrostatic discharge (ESD) is a major source of electromagnetic interference, capable of causing damage, malfunctions, or disruptions in electronic devices. As a result, ESD immunity testing is a critical component of electromagnetic compatibility (EMC) standards. In this study, the radiation emitted from the ESD gun body over 2 GHz is characterized and modeled using Huygens' principle. The equivalent field source was validated across three different environments, demonstrating accuracy with errors of less than 10 dB. A coupling path visualization technique was then employed to identify critical coupling paths, providing guidance for the strategic placement of absorbers. Simulation results showed that …


Improved Optimal Tracking Of Uncertain Nonlinear Discrete-Time Systems Using Experience Replay, Maxwell Geiger, Sarangapani Jagannathan Jan 2025

Improved Optimal Tracking Of Uncertain Nonlinear Discrete-Time Systems Using Experience Replay, Maxwell Geiger, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper addresses the infinite horizon optimal tracking control problem for partially uncertain control-affine nonlinear discrete-time (DT) systems, where the control input dynamics are known. Multi-layer critic and actor neural networks (MNNs) are utilized for online estimation of the infinite horizon value function and optimal control input. The NN weights are tuned online using a direct temporal difference error (TDE)-driven learning approach, which modifies the singular values of the gradient with respect to the NN weights to accelerate their convergence. The critic NN uses a novel experience replay technique to improve sample efficiency without introducing biased TDEs and guarantee the …


Aperture-Based Fss For Dielectric Thickness Sensing, Alexander Hook, Gage Donahue, Kristen M. Donnell Jan 2025

Aperture-Based Fss For Dielectric Thickness Sensing, Alexander Hook, Gage Donahue, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Frequency selective surfaces (FSSs) are planar arrays of patch- or aperture-based elements that have a particular transmissive or reflective response. As FSS performance is affected by changes in the local (to the FSS) environment, FSSs may be used to detect changes in strain, temperature, or nearby material (substructure) thickness, amongst other parameters. To this end, an aperture-based FSS can be considered as a sensor for substructure thickness monitoring for surface mounted sensing scenarios. An aperture-based design was selected due to its ability to operate in reflection mode (and hence a one-sided measurement) without the need for a conductive backplane. In …


Dual Parameter Fss-Based Sensing For Structural Health Monitoring Applications, Swathi Muthyala Ramesh, Doyle T. Motes, Kristen M. Donnell Jan 2025

Dual Parameter Fss-Based Sensing For Structural Health Monitoring Applications, Swathi Muthyala Ramesh, Doyle T. Motes, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

frequency selective surfaces (FSSs) are periodic arrays of conductive elements or apertures that reflect and/or transmit incident electromagnetic energy. Their response depends on parameters, such as element shape, unit cell dimensions, dielectric properties, and the local environment, making them suitable for structural health monitoring (SHM) applications. This article presents a dual-parameter FSS-based sensor design capable of measuring small-scale uni-directional longitudinal strain (0%–0.5%) and temperature (23 ◦C–223 ◦C). The sensor integrates two-unit cells: 1) a patch-based cell on a thin substrate for strain sensing, offering enhanced strain transfer and superior sensitivity (~16–18 MHz/0.1%) and 2) a loop-based cell with a temperature-sensitive …


Analytical Model Of The Ac-Ac Dab Converter In The Egam Framework, Arnold A. Fernandes, Kartikeya Jayadurga Prasad Veeramraju, Jonathan W. Kimball Jan 2025

Analytical Model Of The Ac-Ac Dab Converter In The Egam Framework, Arnold A. Fernandes, Kartikeya Jayadurga Prasad Veeramraju, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

This paper develops an analytical model of the bidirectional AC-AC Dual Active Bridge (DAB) converter. The passive components of the AC-AC DAB are subject to grid, switching, and sideband harmonics. Thus, it is impossible to model via the conventional Generalized Average Method (GAM). It has been numerically shown that Extended GAM (EGAM) can be used to model the AC-AC DAB converter. In this paper, an analytical sixteenth order EGAM-model has been developed that considers only grid harmonics at the filter components and only sideband harmonics for the transformer leakage inductor. A closed-form expression is developed for the 2D convolution product. …


Active Microwave-Thermographic Signal Reconstruction With Adaptive Polynomial Regression, Logan M. Wilcox, Alexander Hook, Emma T. Bohannon, Kristen M. Donnell Jan 2025

Active Microwave-Thermographic Signal Reconstruction With Adaptive Polynomial Regression, Logan M. Wilcox, Alexander Hook, Emma T. Bohannon, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Active microwave thermography (AMT) is a coupled electromagnetic (EM) and thermographic nondestructive testing and evaluation (NDT&E) technique. AMT utilizes a radiating EM source (e.g., an antenna) that induces dielectric/magnetic heating on a specimen under test (SUT). The inspection surface of the SUT is imaged with an infrared (IR) camera over the inspection time. As the thermal excitation originates from a spatially varying radiated power density, a nonuniform thermal excitation results within (or on the surface of) the SUT that is directly related to this power density. This nonuniform heating causes uncertainty in defect detection and has the potential to lead …


Anti-Jamming Attack Mixed Strategy For Formation Tracking Control Via Game-Theoretical Reinforcement Learning, Lei Xue, Bei Ma, Yongbao Wu, Jian Liu, Chaoxu Mu, Donald C. Wunsch Jan 2025

Anti-Jamming Attack Mixed Strategy For Formation Tracking Control Via Game-Theoretical Reinforcement Learning, Lei Xue, Bei Ma, Yongbao Wu, Jian Liu, Chaoxu Mu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Communication plays a role in multi-UAV to perform formation tracking missions. In complex environments, UAV communication is often subject to jamming attacks, affecting the formation process. Therefore, studying the formation tracking control problem in jamming attacks is of great significance. Typically, the actions of the UAV consist of two fundamental modules: mobility strategy and communication strategy. In this paper, we design an anti-jamming attack mixed strategy for formation tracking control of the multi-UAV system. In practical scenarios, multi-UAV systems not only require the accomplishment of formation maneuvers but also necessitate effective mitigation of jamming attacks caused by other UAVs. Therefore, …


Multi-Dimensional Iot-Based Energy Management Approach For Smart Homes: A Unified Model For Comfort And Energy Efficiency, Muhammad Ans, Teodoro Montanaro, Ilaria Sergi, Ahmad Alsharoa, Miriam Pezzuto, Luigi Patrono Jan 2025

Multi-Dimensional Iot-Based Energy Management Approach For Smart Homes: A Unified Model For Comfort And Energy Efficiency, Muhammad Ans, Teodoro Montanaro, Ilaria Sergi, Ahmad Alsharoa, Miriam Pezzuto, Luigi Patrono

Electrical and Computer Engineering Faculty Research & Creative Works

As smart home technologies evolve, achieving energy-efficient indoor climate management while maintaining comfort and air quality is a growing priority. This paper introduces a novel optimization framework for smart buildings that minimizes energy costs and dynamically manages indoor environmental conditions, specifically temperature, CO2 concentration, and illuminance. Unlike conventional systems, our model incorporates dynamic constraints that respond to day-night comfort requirements and leverage real-time variations in electricity prices and environmental conditions. By optimally controlling the power levels of air conditioning, air purification, and lighting systems, the framework ensures indoor comfort while significantly reducing operational costs.A nonlinear optimization approach with dynamic …


Aperiodically Intermittent Dynamic Event-Triggered Control For Predefined-Time Synchronization Of Stochastic Complex Networks, Lei Xue, Haoyu Zhou, Yongbao Wu, Jian Liu, Donald C. Wunsch Jan 2025

Aperiodically Intermittent Dynamic Event-Triggered Control For Predefined-Time Synchronization Of Stochastic Complex Networks, Lei Xue, Haoyu Zhou, Yongbao Wu, Jian Liu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, the problem of practical predefined-time synchronization in mean square (PTSMS) of stochastic complex networks (SCNs) is investigated through dynamic event-triggered control (E-TC). Different from the existing literature, this paper considers the dynamic E-TC in an a periodically intermittent control framework and employs the average control rate, which makes it easier to satisfy the conditions of the theorem. In comparison to existing finite-time and fixed-time synchronization, by introducing the time-varying function, it can be guaranteed that all states of SCNs achieve the practical PTSMS within a preset time without calculating the convergence time. Combined with stochastic analysis theory, …


Discrimination Of Temperature And Strain By Characterizing Two Femtosecond Laser-Written Coincident Sapphire Fiber Bragg Gratings For Harsh Environment Applications, Farhan Mumtaz, Bohong Zhang, Koustav Dey, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang Jan 2025

Discrimination Of Temperature And Strain By Characterizing Two Femtosecond Laser-Written Coincident Sapphire Fiber Bragg Gratings For Harsh Environment Applications, Farhan Mumtaz, Bohong Zhang, Koustav Dey, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

In this study, two co-incident sapphire fiber Bragg gratings (SFBGs) were successfully inscribed utilizing a femtosecond (fs) laser to achieve a high fringe contrast interferogram. These two SFBGs employ a unique configuration, one parallel to the center axis, called p-SFBG, and the other forming an angle from the center-axis, called a-SFBG, allowing for simultaneous strain and temperature measurements with low crosstalk. As a proof of concept, p-SFBG and a-SFBG using line-by-line method are characterized, which are shorter in length (i.e., 1.5 mm), producing reflectivity of ~3dB. This effort demonstrates the use of two coincident SFBGs forming an angle of 2.29° …


Safe Optimal Control Of Quadrotor Formations Using Multilayer Neural Networks And Continual Learning, Ehsan Soleimani, Irfan Ahmad Ganie, S. Jagannathan Jan 2025

Safe Optimal Control Of Quadrotor Formations Using Multilayer Neural Networks And Continual Learning, Ehsan Soleimani, Irfan Ahmad Ganie, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article presents an integral reinforcement learning-based optimal formation tracking scheme for multiple quadrotors unmanned aerial vehicles (QUAVs) experiencing nonlinear coupled dynamics and subject to constraints. We use multilayer neural networks (MNN) within an actor-critic framework where the MNN weights are tuned using singular value decomposition (SVD) of the activation function gradient to approximate optimal control policy via backstepping. Additionally, barrier Lyapunov functions (BLF) are introduced to ensure set invariance, thereby maintaining the quadrotors within a defined safety space due to constraints. A novel weight update law for each layer is derived using the HJB approximation error and control input …


Prescribed-Time Nash Equilibrium Seeking For Pursuit-Evasion Game Under Intermittent Control With Undirected/Directed Graph, Lei Xue, Jianfeng Ye, Yongbao Wu, Jian Liu, D. C. Wunsch Jan 2025

Prescribed-Time Nash Equilibrium Seeking For Pursuit-Evasion Game Under Intermittent Control With Undirected/Directed Graph, Lei Xue, Jianfeng Ye, Yongbao Wu, Jian Liu, D. C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This paper studies the prescribed-time Nash equilibrium (PTNE) seeking problem of the pursuit-evasion game (PEG) with second-order dynamics under the intermittent control (IC) strategy. To achieve Nash equilibrium (NE) in a user-defined prescribed-time, a time-varying high-gain function is incorporated into the design. The core challenge lies in applying IC to NE seeking, which complicates the convergence analysis and control design. To address this sticking point, we construct an auxiliary function and propose a Lyapunov function considering second-order dynamics to solve the PTNE seeking problem of PEG. Building upon the results for undirected graphs, we further extend our findings to directed …