Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons™

Open Access. Powered by Scholars. Published by Universities.®

Electrical and Computer Engineering

Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 4921 - 4950 of 36813

Full-Text Articles in Engineering

Memory-Based Adaptive Sliding Mode Load Frequency Control In Interconnected Power Systems With Energy Storage, Farhad Farivar, Octavian Bass, Daryoush Habibi Jan 2023

Memory-Based Adaptive Sliding Mode Load Frequency Control In Interconnected Power Systems With Energy Storage, Farhad Farivar, Octavian Bass, Daryoush Habibi

Research outputs 2022 to 2026

This paper presents a memory-based adaptive sliding mode load frequency control (LFC) strategy aimed at minimizing the impacts of exogenous power disturbances and parameter uncertainties on frequency deviations in interconnected power systems with energy storage. First, the dynamic model of the system is constructed by considering the participation of the energy storage system (ESS) in the conventional decentralized LFC model of a multiarea power system. A disturbance observer (DOB) is proposed to generate an online approximation of the lumped disturbance. In order to enhance the transient performance of the system and effectively mitigate the adverse effects of power fluctuations on …

Go to article

Cooperative Deep $Q$ -Learning Framework For Environments Providing Image Feedback, Krishnan Raghavan, Vignesh Narayanan, Sarangapani Jagannathan Jan 2023

Cooperative Deep $Q$ -Learning Framework For Environments Providing Image Feedback, Krishnan Raghavan, Vignesh Narayanan, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In This Article, We Address Two Key Challenges in Deep Reinforcement Learning (DRL) Setting, Sample Inefficiency and Slow Learning, with a Dual-Neural Network (NN)-Driven Learning Approach. in the Proposed Approach, We Use Two Deep NNs with Independent Initialization to Robustly Approximate the Action-Value Function in the Presence of Image Inputs. in Particular, We Develop a Temporal Difference (TD) Error-Driven Learning (EDL) Approach, Where We Introduce a Set of Linear Transformations of the TD Error to Directly Update the Parameters of Each Layer in the Deep NN. We Demonstrate Theoretically that the Cost Minimized by the EDL Regime is an Approximation …

Go to article

A Resilience-Oriented Multi-Stage Adaptive Distribution System Planning Considering Multiple Extreme Weather Events, Siyuan Wang, Rui Bo Jan 2023

A Resilience-Oriented Multi-Stage Adaptive Distribution System Planning Considering Multiple Extreme Weather Events, Siyuan Wang, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Climate Change May Increase the Risk of an Area Being Hit by Multiple Extreme Weather Events, Which Brings Significant Challenges for Distribution System Planners in an Increasing Renewable Penetration Era. There is an Urgent Need for Planning Approaches to Be More Flexible and Allow for Adaptive Adjustments in the Future to Hedge Against High Uncertainties in Extreme Weather Event Scenarios. in This Work, We Propose a Resilience-Oriented Distribution System Planning Approach that Considers Multiple Extreme Weather Events. a Multi-Stage Hybrid-Stochastic-And-Robust Formulation is Developed to Model Decisions Not Only for Initial Investments, But Also for Adaptive Investments and Emergent Operations in …

Go to article

Extended Kalman Filter Based Resilient Formation Tracking Control Of Multiple Unmanned Vehicles Via Game-Theoretical Reinforcement Learning, Lei Xue, Bei Ma, Jian Liu, Chaoxu Mu, Donald C. Wunsch Jan 2023

Extended Kalman Filter Based Resilient Formation Tracking Control Of Multiple Unmanned Vehicles Via Game-Theoretical Reinforcement Learning, Lei Xue, Bei Ma, Jian Liu, Chaoxu Mu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

In This Paper, We Discuss the Resilient Formation Tracking Control Problem of Multiple Unmanned Vehicles (MUV). a Dynamic Leader-Follower Distributed Control Structure is Utilized to Optimize the Performance of the Formation Tracking. for the Follower of the MUV, the Leader is a Cooperative Unmanned Vehicle, and the Target of Formation Tracking is a Non-Cooperative Unmanned Vehicle with a Nonlinear Trajectory. Therefore, an Extended Kalman Filter (EKF) Observer is Designed to Estimate the State of the Target. Then the Leader of the MUV is Adjusted Dynamically According to the State of the Target. in Order to Describe the Interactions between the …

Go to article

A Throughput Fast Measurement Method For Two-Antenna Equipped Wireless Mimo Terminals, Penghui Shen, Quan Yu, Daryl G. Beetner, Yihong Qi Jan 2023

A Throughput Fast Measurement Method For Two-Antenna Equipped Wireless Mimo Terminals, Penghui Shen, Quan Yu, Daryl G. Beetner, Yihong Qi

Electrical and Computer Engineering Faculty Research & Creative Works

According to the Third Generation Partnership Project Specification, a Period of 8-12.8 H is Required to Evaluate the Multiple-Input-Multiple-Output (MIMO) Performance of a Wireless Terminal for a Single Frequency Point and Channel Model Combination. the Following Article Proposes a Semi-Simulation, Semi-Measurement-Based MIMO throughput Modeling Scheme Which Can Reduce the 8-12.8-H Measurement Time to 40-60 Min, Corresponding to More Than a Ten Times Improvement of the Test Efficiency, Without Loss of the Test Accuracy.

Go to article

Averaged Behavior Model Of Current-Mode Buck Converters For Transient Power Noise Analysis, Anfeng Huang, Jingdong Sun, Hongseok Kim, Zhenxue Xu, Shuai Jin, Songping Wu, Zhiping Yang, Kelvin Qiu, Jun Fan, Chulsoon Hwang Jan 2023

Averaged Behavior Model Of Current-Mode Buck Converters For Transient Power Noise Analysis, Anfeng Huang, Jingdong Sun, Hongseok Kim, Zhenxue Xu, Shuai Jin, Songping Wu, Zhiping Yang, Kelvin Qiu, Jun Fan, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate Evaluation and Simulation of Power Noise is Critical in the Development of Modern Electronic Devices. However, the Widely Used Target Impedance Fails to Predict the Low-Frequency Noise Generated in a Device Due to the Existence of the Dc–dc Converter, Whose Output Impedance Can Change under Different Loading Conditions. a Physical Circuit Model is Then Desired to Replicate the Behavior of a Voltage Regulator Module, and the Average Technique is an Efficient Method to Estimate the Noise of a Pulse Width-Modulated (PWM) Converter. with the Emergence of Converters with Adaptive On-Time (AOT) Controllers, More Complex Averaging Methods Are Required, But …

Go to article

Methodology For Analyzing Coupling Mechanisms In Rfi Problems Based On Peec, Xu Wang, Anfeng Huang, Wei Zhang, Reza Yazdani, Donghyun Kim, Takashi Enomoto, Taketoshi Sekine, Kenji Araki, Jun Fan, Chulsoon Hwang Jan 2023

Methodology For Analyzing Coupling Mechanisms In Rfi Problems Based On Peec, Xu Wang, Anfeng Huang, Wei Zhang, Reza Yazdani, Donghyun Kim, Takashi Enomoto, Taketoshi Sekine, Kenji Araki, Jun Fan, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

In This Article, a Method for Analyzing Coupling Mechanisms in Radio Frequency Interference (RFI) Problems is Proposed. the Partial Element Equivalent Circuit (PEEC) Method is First Used to Derive the Retarded Inductances and Capacitances between Different Mesh Cells. with the Introduction of a Novel Partitioning Algorithm, the Capacitive Coupling and Inductive Coupling between Arbitrary Layout Parts Can Be Quantified based on the Magnitude of the Displacement Current and Induced Voltage Drop. the Accuracy of the PEEC Models is Validated by Comparison with Different Commercial Tools. the Proposed Coupling Mechanism Analysis Flow Provides a Useful Prelayout Tool for RFI Risk Analysis.

Go to article

Embeddable Soil Moisture Content Sensor Based On Open–End Microwave Coaxial Cable Resonator, Jing Guo, Yan Tang, Yongji Wu, Chen Zhu, Jie Huang Jan 2023

Embeddable Soil Moisture Content Sensor Based On Open–End Microwave Coaxial Cable Resonator, Jing Guo, Yan Tang, Yongji Wu, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

In This Paper, We Propose and Demonstrate a Novel Corrosion-Resistant, Embeddable Open-End Coaxial Cable Soil Moisture Sensor. This Microwave Resonator is Constructed using Two Reflectors Along the Coaxial Line. the First Reflector is a Metal Post at the Signal Input End, Short-Circuiting the Inner Conductor to the Outer Conductor. the Second Reflector Comprises a Welded Metal Plate Parallel to the Open-End of the Coaxial Line, Maintaining a Fixed Gap. a Moisture-Sensitive Polyvinyl Alcohol (PVA) Film is Inserted into This Gap. the Resonance Frequency of the Open-End Coaxial Cable Resonator is Highly Dependent on the Fringe Capacitance, Which Varies with Soil …

Go to article

Electromagnetic Transmit Array With Optical Control For Beamforming, Wei Zhang, Javad Meiguni, Yin Sun, Muqi Ouyang, Xin Yan, Xu Wang, Reza Yazdani, Daryl G. Beetner, Donghyun Kim, David Pommerenke Jan 2023

Electromagnetic Transmit Array With Optical Control For Beamforming, Wei Zhang, Javad Meiguni, Yin Sun, Muqi Ouyang, Xin Yan, Xu Wang, Reza Yazdani, Daryl G. Beetner, Donghyun Kim, David Pommerenke

Electrical and Computer Engineering Faculty Research & Creative Works

This Proof-Of-Concept Paper Demonstrates the Feasibility of using a Slide Projector to Steer the Beam of a Transmit Array by Adding Solar Cells and Varactor Diodes to Each Unit Cell. by Irradiating Each Solar Cell with the Light of Different Intensities from a Slide Projector, the Measured Phase of the Wave Transmitted by the 4x4 Transmit Array Shifts within 92° at 4.26 GHz, While the Variation in Magnitude is Measured within 4 DB. Different Light Configurations Are Identified Via a Searching Algorithm to Achieve Peak/null Beamforming in a Particular Direction. the Beam of the Prototypical 4x4 Transmit Array Can Be …

Go to article

Predicting Dissolution Kinetics Of Tricalcium Silicate Using Deep Learning And Analytical Models, Taihao Han, Sai Akshay Ponduru, Arianit Reka, Jie Huang, Gaurav Sant, Aditya Kumar Jan 2023

Predicting Dissolution Kinetics Of Tricalcium Silicate Using Deep Learning And Analytical Models, Taihao Han, Sai Akshay Ponduru, Arianit Reka, Jie Huang, Gaurav Sant, Aditya Kumar

Electrical and Computer Engineering Faculty Research & Creative Works

The dissolution kinetics of Portland cement is a critical factor in controlling the hydration reaction and improving the performance of concrete. Tricalcium silicate (C3S), the primary phase in Portland cement, is known to have complex dissolution mechanisms that involve multiple reactions and changes to particle surfaces. As a result, current analytical models are unable to accurately predict the dissolution kinetics of C3S in various solvents when it is undersaturated with respect to the solvent. This paper employs the deep forest (DF) model to predict the dissolution rate of C3S in the undersaturated solvent. The …

Go to article

Predicting Compressive Strength And Hydration Products Of Calcium Aluminate Cement Using Data-Driven Approach, Sai Akshay Ponduru, Taihao Han, Jie Huang, Aditya Kumar Jan 2023

Predicting Compressive Strength And Hydration Products Of Calcium Aluminate Cement Using Data-Driven Approach, Sai Akshay Ponduru, Taihao Han, Jie Huang, Aditya Kumar

Electrical and Computer Engineering Faculty Research & Creative Works

Calcium aluminate cement (CAC) has been explored as a sustainable alternative to Portland cement, the most widely used type of cement. However, the hydration reaction and mechanical properties of CAC can be influenced by various factors such as water content, Li2CO3 content, and age. Due to the complex interactions between the precursors in CAC, traditional analytical models have struggled to predict CAC binders' compressive strength and porosity accurately. To overcome this limitation, this study utilizes machine learning (ML) to predict the properties of CAC. The study begins by using thermodynamic simulations to determine the phase assemblages of …

Go to article

Real-Time Air Gap And Thickness Measurement Of Continuous Caster Mold Flux By Extrinsic Fabry-Perot Interferometer, Abhishek Prakash Hungund, Hanok Tekle, Bohong Zhang, Ronald J. O'Malley, Jeffrey D. Smith, Rex E. Gerald, Jie Huang Jan 2023

Real-Time Air Gap And Thickness Measurement Of Continuous Caster Mold Flux By Extrinsic Fabry-Perot Interferometer, Abhishek Prakash Hungund, Hanok Tekle, Bohong Zhang, Ronald J. O'Malley, Jeffrey D. Smith, Rex E. Gerald, Jie Huang

Materials Science and Engineering Faculty Research & Creative Works

Mold Flux plays a critical role in continuous casting of steel. Along with many other functions, the mold flux in the gap between the solidifying steel shell and the mold serves as a medium for controlling heat transfer and as a barrier to prevent shell sticking to the mold. This manuscript introduces a novel method of monitoring the structural features of a mold flux film in real-time in a simulated mold gap. A 3-part stainless-steel mold was designed with a 2 mm, 4 mm and, 6 mm step profile to contain mold flux films of varying thickness. An Extrinsic Fabry-Perot …

Go to article

Managing Reserve Deliverability Risk Of Integrated Electricity-Heat Systems In Day-Ahead Market: A Distributionally Robust Joint Chance Constrained Approach, Yang Chen, Jianxue Wang, Siyuan Wang, Rui Bo, Chenjia Gu, Qingtao Li Jan 2023

Managing Reserve Deliverability Risk Of Integrated Electricity-Heat Systems In Day-Ahead Market: A Distributionally Robust Joint Chance Constrained Approach, Yang Chen, Jianxue Wang, Siyuan Wang, Rui Bo, Chenjia Gu, Qingtao Li

Electrical and Computer Engineering Faculty Research & Creative Works

The integrated electricity and heat system (IEHS) is an emerging demand-side flexible resource for power systems. IEHS operators participating in electricity markets considering their capabilities in reserve provision will face the reserve deliverability risk due to the energy-limited storage nature of heat systems. To address this challenge and increase profitability, a distributionally robust joint chance-constrained mechanism with enhanced quantifications is adopted for the heating system and reserve deployment uncertainties. Detailed pipeline storage representation for thermal networks and integrated demand response are incorporated into this strategic participation model. A two-stage distributionally robust joint chance constrained program is then incorporated to effectively …

Go to article

Observer-Based Model Predictive Control With Continuous Control Set For Single-Phase Rectifiers, Milad Dehghanzadeh, Rui Bo, Kamal Al-Haddad Jan 2023

Observer-Based Model Predictive Control With Continuous Control Set For Single-Phase Rectifiers, Milad Dehghanzadeh, Rui Bo, Kamal Al-Haddad

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a model predictive controller (MPC) is designed for a single-phase rectifier. The proposed MPC works with a continuous control set (CCS) that addresses variable switching issues in finite control set (FCS) MPCs. The observe-ability of the rectifier enables the design of a full-state observer to measure only output voltage in which the AC current of the rectifier is estimated. Both the proposed controller and observer are assessed with simulation studies and the results show the acceptable performance of the observer and CCS-MPC as well as good disturbance rejection in load and network parameter variations.

Go to article

Dipole-Moment-Based Reciprocity For Practical Desensitization Identification And Mitigation, Shengxuan Xia, Hanfeng Wang, Yansheng Wang, Zhonghua Wu, Chulsoon Hwang, Jun Fan Jan 2023

Dipole-Moment-Based Reciprocity For Practical Desensitization Identification And Mitigation, Shengxuan Xia, Hanfeng Wang, Yansheng Wang, Zhonghua Wu, Chulsoon Hwang, Jun Fan

Electrical and Computer Engineering Faculty Research & Creative Works

Radio frequency interference can degrade the receiving sensitivity of antennas. The interference is usually caused by certain coupling structures, such as layouts without adequate grounding for the radio frequency signal return path. Those structures can be modeled as a set of equivalent dipole moments when they are electrically small. Herein, the dipole moment model-based coupling framework is applied to a practical cellphone design case to devise an engineering solution. The coupling framework incorporates dipole moments as radiation sources and a coupling model based on the reciprocity theorem. Unfortunately, near-field scan probes often lack access to all locations, owing to the …

Go to article

Sample Considerations For Short-Circuited Filled Transmission Line Measurements, Jared Sinkey, Alexander Hook, Kristen M. Donnell Jan 2023

Sample Considerations For Short-Circuited Filled Transmission Line Measurements, Jared Sinkey, Alexander Hook, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Microwave materials characterization can be performed using a number of well-established measurement approaches. One such approach, the short-circuited rectangular waveguide (SC-RWG) filled transmission line approach, is known to have sample placement restrictions related to measurement reliability. This work focuses on this approach as a viable solution for microwave materials characterization of liquid materials and addresses the measurement restrictions within the context of sample length and dielectric properties. It is shown via simulation and measurement that samples of length greater than g/6 (where g is the wavelength in the RWG) do not have the reported measurement restrictions, nor do materials with …

Go to article

A Methodology For Predicting Acoustic Noise From Singing Capacitors In Mobile Devices, Xin Yan, Jianmin Zhang, Songping Wu, Ming Feng Xue, Chi Kin Benjamin Leung, Eric A. Macintosh, Daryl G. Beetner Jan 2023

A Methodology For Predicting Acoustic Noise From Singing Capacitors In Mobile Devices, Xin Yan, Jianmin Zhang, Songping Wu, Ming Feng Xue, Chi Kin Benjamin Leung, Eric A. Macintosh, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Multilayer ceramic capacitors (MLCCs) connected to a power distribution network (PDN) can create acoustic noise through a combination of the power rail noise at the MLCCs and the piezoelectric effect of the capacitor's ceramic material. The deformation of the MLCCs brought on by power supply noise creates vibrations which cause the printed circuit board (PCB) to vibrate and generate the audible acoustic noise. In the following paper, a simulation methodology is presented to analyze the acoustic noise created by MLCCs on a PCB. A simulation model for the PCB vibration modal response is built and the modal superposition method is …

Go to article

Distributed Detection Over Blockchain-Aided Internet Of Things In The Presence Of Attacks, Yiming Jiang, Jiangfan Zhang Jan 2023

Distributed Detection Over Blockchain-Aided Internet Of Things In The Presence Of Attacks, Yiming Jiang, Jiangfan Zhang

Electrical and Computer Engineering Faculty Research & Creative Works

Distributed detection over a blockchain-aided Internet of Things (BIoT) network in the presence of attacks is considered, where the integrated blockchain is employed to secure data exchanges over the BIoT as well as data storage at the agents of the BIoT. We consider a general adversary model where attackers jointly exploit the vulnerability of IoT devices and that of the blockchain employed in the BIoT. The optimal attacking strategy which minimizes the Kullback-Leibler divergence is pursued. It can be shown that this optimization problem is nonconvex, and hence it is generally intractable to find the globally optimal solution to such …

Go to article

Multi-Point Optical Fiber Fabry-Perot Curvature Sensor Based On Microwave Photonics, Chen Zhu, Ruimin Jie, Osamah Alsalman, Hongkun Zheng, Wassana Naku, Bo Liu, Lingmei Ma Jan 2023

Multi-Point Optical Fiber Fabry-Perot Curvature Sensor Based On Microwave Photonics, Chen Zhu, Ruimin Jie, Osamah Alsalman, Hongkun Zheng, Wassana Naku, Bo Liu, Lingmei Ma

Electrical and Computer Engineering Faculty Research & Creative Works

This article reports a multi-point curvature sensor system based on multiplexed optical fiber Fabry-Perot interferometric (FPI) sensor devices and a microwave photonics interrogation technique. The FPI sensor is fabricated with the assistance of a capillary tube, where a short section of the capillary is sandwiched between two single-mode fibers, forming the airgap Fabry-Perot cavity. Bending of the FPI device leads to changes in the fringe contrast of its reflection spectrum. Based on the microwave photonics filtering technique, variations of the fringe contrast are encoded into the changes in the peak magnitude of the passband in the frequency response of the …

Go to article

Continual Reinforcement Learning Formulation For Zero-Sum Game-Based Constrained Optimal Tracking, Behzad Farzanegan, Sarangapani Jagannathan Jan 2023

Continual Reinforcement Learning Formulation For Zero-Sum Game-Based Constrained Optimal Tracking, Behzad Farzanegan, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This study provides a novel reinforcement learning-based optimal tracking control of partially uncertain nonlinear discrete-time (DT) systems with state constraints using zero-sum game (ZSG) formulation. To address optimal tracking, a novel augmented system consisting of tracking error and its integral value, along with an uncertain desired trajectory, is constructed. A barrier function (BF) with a tradeoff factor is incorporated into the cost function to keep the state trajectories to remain within a compact set and to balance safety with optimality. Next, by using the modified value functional, the ZSG formulation is introduced wherein an actor–critic neural network (NN) framework is …

Go to article

Continual Optimal Adaptive Tracking Of Uncertain Nonlinear Continuous-Time Systems Using Multilayer Neural Networks, Irfan Ganie, S. (Sarangapani) Jagannathan Jan 2023

Continual Optimal Adaptive Tracking Of Uncertain Nonlinear Continuous-Time Systems Using Multilayer Neural Networks, Irfan Ganie, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This study provides a lifelong integral reinforcement learning (LIRL)-based optimal tracking scheme for uncertain nonlinear continuous-time (CT) systems using multilayer neural network (MNN). In this LIRL framework, the optimal control policies are generated by using both the critic neural network (NN) weights and single-layer NN identifier. The critic MNN weight tuning is accomplished using an improved singular value decomposition (SVD) of its activation function gradient. The NN identifier, on the other hand, provides the control coefficient matrix for computing the control policies. An online weight velocity attenuation (WVA)-based consolidation scheme is proposed wherein the significance of weights is derived by …

Go to article

Three-Terminal Noise Source Extraction From A Qi-Based Wireless Power Transfer System For Predicting Conducted Emissions, Srinath Penugonda, Siqi Bai, Varittha Sanphuang, Nevin Altunyurt, Hongseok Kim, Daryl G. Beetner, Jun Fan Jan 2023

Three-Terminal Noise Source Extraction From A Qi-Based Wireless Power Transfer System For Predicting Conducted Emissions, Srinath Penugonda, Siqi Bai, Varittha Sanphuang, Nevin Altunyurt, Hongseok Kim, Daryl G. Beetner, Jun Fan

Electrical and Computer Engineering Faculty Research & Creative Works

An equivalent method to extract a three-terminal noise source from a Qi-based wireless power transfer system is proposed in this article. This method is capable of extracting a source for both the positive (P) and negative (N) lines with respect to the third terminal (the ground chassis or reference plane). The extracted sources are independent of the setup configuration and can be used to predict currents or voltages on the P and N lines on a setup that is different from the extraction setup. In the following article, a three-terminal model independent of the setup configuration is first extracted. The …

Go to article

Investigation Of The Radiation Mechanism Of Heatsinks Based On Characteristic Mode Theory, Xu Wang, Matthew Wu, Jagan Rajagopalan, Akshay Mohan, Donghyun Kim, Chulsoon Hwang Jan 2023

Investigation Of The Radiation Mechanism Of Heatsinks Based On Characteristic Mode Theory, Xu Wang, Matthew Wu, Jagan Rajagopalan, Akshay Mohan, Donghyun Kim, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

Heatsinks may cause radiated emission and radio frequency interference problems when they are mounted on printed circuit boards. In this article, the radiation mechanism of heatsinks is systematically investigated using characteristic mode theory. The dipole moment is a commonly used equivalent source model for integrated circuits that drive radiated emission from heatsinks. On the basis of a simplified modal weighting coefficient formulation, the interactions between the dipole moment and the significant modes of the heatsink are efficiently evaluated, thus providing a clear physical insight into noise source placement. Finally, the grounding post design, a commonly used EMI mitigation method, is …

Go to article

Optimal Tracking Of Nonlinear Discrete-Time Systems Using Zero-Sum Game Formulation And Hybrid Learning, Behzad Farzanegan, S. (Sarangapani) Jagannathan Jan 2023

Optimal Tracking Of Nonlinear Discrete-Time Systems Using Zero-Sum Game Formulation And Hybrid Learning, Behzad Farzanegan, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a novel hybrid learning-based optimal tracking method to address zero-sum game problems for partially uncertain nonlinear discrete-time systems. An augmented system and its associated discounted cost function are defined to address optimal tracking. Three multi-layer neural networks (NNs) are utilized to approximate the optimal control and the worst-case disturbance inputs, and the value function. The critic weights are tuned using the hybrid technique, whose weights are updated once at the sampling instants and in an iterative manner over finite times within the sampling instants. The proposed hybrid technique helps accelerate the convergence of the approximated value functional …

Go to article

Securing The Transportation Of Tomorrow: Enabling Self-Healing Intelligent Transportation, Elanor Jackson, Sahra Sedigh Sarvestani Jan 2023

Securing The Transportation Of Tomorrow: Enabling Self-Healing Intelligent Transportation, Elanor Jackson, Sahra Sedigh Sarvestani

Electrical and Computer Engineering Faculty Research & Creative Works

The safety of autonomous vehicles relies on dependable and secure infrastructure for intelligent transportation. The doctoral research described in this paper aims to enable self-healing and survivability of the intelligent transportation systems required for autonomous vehicles (AV-ITS). The proposed approach is comprised of four major elements: qualitative and quantitative modeling of the AV-ITS, stochastic analysis to capture and quantify interdependencies, mitigation of disruptions, and validation of efficacy of the self-healing process. This paper describes the overall methodology and presents preliminary results, including an agent-based model for detection of and recovery from disruptions to the AV-ITS.

Go to article

Virtual Synchronous Generator Control Using Twin Delayed Deep Deterministic Policy Gradient Method, Oroghene Oboreh-Snapps, Buxin She, Shah Fahad, Haotian Chen, Jonathan W. Kimball, Fangxing Li, Hantao Cui, Rui Bo Jan 2023

Virtual Synchronous Generator Control Using Twin Delayed Deep Deterministic Policy Gradient Method, Oroghene Oboreh-Snapps, Buxin She, Shah Fahad, Haotian Chen, Jonathan W. Kimball, Fangxing Li, Hantao Cui, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a data-driven approach that adaptively tunes the parameters of a virtual synchronous generator to achieve optimal frequency response against disturbances. In the proposed approach, the control variables, namely, the virtual moment of inertia and damping factor, are transformed into actions of a reinforcement learning agent. Different from the state-of-the-art methods, the proposed study introduces the settling time parameter as one of the observations in addition to the frequency and rate of change of frequency (RoCoF). In the reward function, preset indices are considered to simultaneously ensure bounded frequency deviation, low RoCoF, fast response, and quick settling time. …

Go to article

Personalizing Student Graduation Paths Using Expressed Student Interests, Nicolas Dobbins, Ali R. Hurson, Sahra Sedigh Jan 2023

Personalizing Student Graduation Paths Using Expressed Student Interests, Nicolas Dobbins, Ali R. Hurson, Sahra Sedigh

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes an intelligent recommendation approach to facilitate personalized education and help students in planning their path to graduation. The goal is to identify a path that aligns with a student's interests and career goals and approaches optimality with respect to one or more criteria, such as time-to-graduation or credit hours taken. The approach is illustrated and verified through application to undergraduate curricula at the Missouri University of Science and Technology.

Go to article

Optimal Adaptive Tracking Control Of Partially Uncertain Nonlinear Discrete-Time Systems Using Lifelong Hybrid Learning, Behzad Farzanegan, Rohollah Moghadam, Sarangapani Jagannathan, Pappa Natarajan Jan 2023

Optimal Adaptive Tracking Control Of Partially Uncertain Nonlinear Discrete-Time Systems Using Lifelong Hybrid Learning, Behzad Farzanegan, Rohollah Moghadam, Sarangapani Jagannathan, Pappa Natarajan

Electrical and Computer Engineering Faculty Research & Creative Works

This article addresses a multilayer neural network (MNN)-based optimal adaptive tracking of partially uncertain nonlinear discrete-time (DT) systems in affine form. By employing an actor–critic neural network (NN) to approximate the value function and optimal control policy, the critic NN is updated via a novel hybrid learning scheme, where its weights are adjusted once at a sampling instant and also in a finite iterative manner within the instants to enhance the convergence rate. Moreover, to deal with the persistency of excitation (PE) condition, a replay buffer is incorporated into the critic update law through concurrent learning. To address the vanishing …

Go to article

Miniature Optical Fiber-Tip High-Temperature Sensors Modified By Femtosecond Laser, Chen Zhu, Jie Huang Jan 2023

Miniature Optical Fiber-Tip High-Temperature Sensors Modified By Femtosecond Laser, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Miniature optical fiber-tip Fabry-Perot interferometric sensors fabricated by femtosecond laser micromachining for eliminating the additional Fresnel reflection and avoiding complicated amplitude modulation in the reflection spectra are demonstrated.

Go to article

Enhancing Near-Field Wireless Localization With Lidar-Assisted Ris In Multipath Environments, Omar Rinch, Ahmed Elzanaty, Ahmad Alsharoa Jan 2023

Enhancing Near-Field Wireless Localization With Lidar-Assisted Ris In Multipath Environments, Omar Rinch, Ahmed Elzanaty, Ahmad Alsharoa

Electrical and Computer Engineering Faculty Research & Creative Works

In Next-Generation Wireless Networks that Adopt Millimeter-Waves and Large RIS, the User is Expected to Be in the Near-Field Region, Where the Widely Adopted Far-Field Algorithms based on Far-Field Can Yield Low Positioning Accuracy. Also, the Localization of UE Becomes More Challenging in Multipath Environments. in This Paper, We Propose a Localization Algorithm for a UE in the Near-Field of a RIS in Multipath Environments. the Proposed Scheme Utilizes a LiDAR to Assist the UE Positioning by Providing Geometric Information About Some of the Scatterers in the Environment. This Information is Fed to a Sparse Recovery Algorithm to Improve the …

Go to article

First Prev Next Last