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An Insight Into The Effect Of Sharp And Round Edges On The Flow Field-A Cfd Simulation, Abid Hussain, Gao Puzhen, M. Mustafa Azeem, Muhammad Zubair, Muhammad Aamir, Muhammad Irfan Khaleed Jan 2023

An Insight Into The Effect Of Sharp And Round Edges On The Flow Field-A Cfd Simulation, Abid Hussain, Gao Puzhen, M. Mustafa Azeem, Muhammad Zubair, Muhammad Aamir, Muhammad Irfan Khaleed

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This paper presents a numerical investigation of pressure drop and distribution in a channel around a sharp edge and a disc that is connected to the base of a circular rod. We have employed computational fluid dynamics (CFD)-Fluent for the validation of our models. It was found that the edge sharpness of the disc influences the pressure drop., i.e. sharp edge has higher turbulence and pressure drop. We also observed that pressure drops in the case of the circular disc are less than that of the sharp edge. However, pressure drop has essentially the same values for both shapes after …

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Analytical And Numerical Behavior Of Double Composite Steel Bridges, Emad M. Hassan, Hussam Mahmoud Jan 2023

Analytical And Numerical Behavior Of Double Composite Steel Bridges, Emad M. Hassan, Hussam Mahmoud

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Steel plate girders are considered a viable solution for the construction of medium- to long-span bridges. Despite their many advantages, various concerns have been raised regarding their maintenance due to the potential of fatigue crack initiation at welded details, accelerated corrosion in thin webs, and trapped debris around stiffeners. The use of rolled beams, on the other hand, can be very beneficial because they require much less maintenance. However, they are limited in size, which imposes constraints on their use to relatively short-span bridges due to deflection requirements. In this study, the behavior of the double composite superstructure system was …

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Measurement Of Volumetric Deformation, Strain Localization, And Shear Band Characterization During Triaxial Testing Using A Photogrammetry-Based Method, Sara Fayek, Xiong Zhang, Xiaolong Xia, Qingqing Fu, Jeffrey D. Cawlfield Jan 2023

Measurement Of Volumetric Deformation, Strain Localization, And Shear Band Characterization During Triaxial Testing Using A Photogrammetry-Based Method, Sara Fayek, Xiong Zhang, Xiaolong Xia, Qingqing Fu, Jeffrey D. Cawlfield

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Triaxial Testing Has Been Routinely Used as a Standard Laboratory Test that Allows Correct Determination of Soil Characteristics. Previously the Volumetric Strain of the Triaxial Specimen Was Considered to Be Uniformly Distributed Along with the Specimen during the Isotropic and Deviatoric Loading. Although This Assumption Might Hold True under Isotropic Loading, the Effects of Restrained Ends and Disturbance during the Procedures of Specimen Installation and Testing Can Cause Nonuniform Strains throughout the Whole Specimen. This Paper Investigates the Effects of Specimen Preparation and Misalignment on the Strain Uniformity Along with the Soil Specimen during Triaxial Testing. a Series of Consolidated …

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Analyzing Ground Motion Records With Cvi Fuzzy Art, Dustin Tanksley, Xinzhe Yuan, Genda Chen, Donald C. Wunsch Jan 2023

Analyzing Ground Motion Records With Cvi Fuzzy Art, Dustin Tanksley, Xinzhe Yuan, Genda Chen, Donald C. Wunsch

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This paper explores using Cluster Validity Indices Fuzzy Adaptative Resonance Theory (CVI Fuzzy ART) to cluster ground motion records (GMRs). Clustering the features extracted from a supervised network trained for predicting the structure damage results in less overfitting from the trained network. Using Cluster Validity Indices (CVIs) to evaluate the clustering gives feedback to how well the data is being classified, allowing further separation of the data. By using CVI Fuzzy ART in combination with features extracted from a trained Convolutional Neural Network (CNN), we were able to form additional clusters in the data. Within the primary clusters, accuracy was …

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Approximation Of Optimal Control Surfaces For The Bass Model With Stochastic Dynamics, Gabriel Nicolosi, Christopher Griffin Jan 2023

Approximation Of Optimal Control Surfaces For The Bass Model With Stochastic Dynamics, Gabriel Nicolosi, Christopher Griffin

Engineering Management and Systems Engineering Faculty Research & Creative Works

The Bass diffusion equation is a well-known and established modeling approach for describing new product adoption in a competitive market. This model also describes diffusion phenomena in various contexts: infectious disease spread modeling and estimation, rumor spread on social networks, prediction of renewable energy technology markets, among others. Most of these models, however, consider a deterministic trajectory of the associated state variable (e.g., market-share). In reality, the diffusion process is subject to noise, and a stochastic component must be added to the state dynamics. The stochastic Bass model has also been studied in many areas, such as energy markets and …

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Usdot Tier-1 University Transportation Center For Advancing Cybersecurity Research And Education, Yunpeng Jack Zhang, Kailai Wang, Lingguang Song, Amaury Lendasse, Houbing Herbert Song, Zhu Han, Rakesh Verma, Arlei Silva, Carlos Rubio-Medrano, Zhixia Richard Li, Guohui Zhang Jan 2023

Usdot Tier-1 University Transportation Center For Advancing Cybersecurity Research And Education, Yunpeng Jack Zhang, Kailai Wang, Lingguang Song, Amaury Lendasse, Houbing Herbert Song, Zhu Han, Rakesh Verma, Arlei Silva, Carlos Rubio-Medrano, Zhixia Richard Li, Guohui Zhang

Engineering Management and Systems Engineering Faculty Research & Creative Works

The Transportation Cybersecurity Center for Advanced Research and Education (Cyber-Care) is a Us Department of Transportation (Usdot) Tier-1 University Transportation Center (Utc) Funded in 2023. Cyber-Care Primarily Focuses on the Usdot Statutory Research Priority Area of 'reducing Transportation Cybersecurity Risks.' Cyber-Care Aims to Establish a Fundamental Knowledge Basis and Explore Advanced Theory to Mitigate the Impacts of Large-Scale Cyberattacks on Transportation Infrastructure and Connected and Automated Vehicle (Cav) Systems. the Research Projects at Cyber-Care Will Develop Conceptual Frameworks, Construct Comprehensive Datasets, Explore Novel Analytical Approaches, Support the Implementation of Public Policies and Infrastructure Investments, and Build a High-Quality Industry Workforce …

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Decentralized And Coordinated V-F Control For Islanded Microgrids Considering Der Inadequacy And Demand Control, Buxin She, Fangxing Li, Hantao Cui, Jinning Wang, Liang Min, Oroghene Oboreh-Snapps, Rui Bo Jan 2023

Decentralized And Coordinated V-F Control For Islanded Microgrids Considering Der Inadequacy And Demand Control, Buxin She, Fangxing Li, Hantao Cui, Jinning Wang, Liang Min, Oroghene Oboreh-Snapps, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

This Paper Proposes a Decentralized and Coordinated Voltage and Frequency (V-F) Control Framework for Islanded Microgrids, with Full Consideration of the Limited Capacity of Distributed Energy Resources (DERs) and V-F Dependent Load. First, the Concept of DER Inadequacy is Illustrated with the Challenges It Poses. Then, a Decentralized and Coordinated Control Framework is Proposed to Regulate the Output of Inverter-Based Generations and Reallocate Limited DER Capacity for V-F Control. the Control Framework is Composed of a Power Regulator and a V-F Regulator, Which Generates the Supplementary Signals for the Primary Controller. the Power Regulator Regulates the Output of Grid-Forming Inverters …

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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 …

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An Extended Generalized Average Modeling Framework For Power Converters, Kartikeya Jayadurga Prasad Veeramraju, Jacob A. Mueller, Jonathan W. Kimball Jan 2023

An Extended Generalized Average Modeling Framework For Power Converters, Kartikeya Jayadurga Prasad Veeramraju, Jacob A. Mueller, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

The Generalized Averaged Modeling (GAM) technique is traditionally employed to capture the dynamic performance of power electronic converters. This paper proposes an improved version of it, named the Extended-GAM (EGAM) technique, which supports the multiplication of two Double Fourier Series (DFS) signals in the time domain. Multiplication of DFS signals in the time domain translates to the 2D-convolution of coefficients of the DFS terms of their equivalent Discrete Fourier Image (DFI) representations. Thus, the proposed EGAM technique, capable of capturing many harmonics present in the output of a power converter, effectively captures the dynamic behavior of power converters excited by …

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Inverter Pq Control With Trajectory Tracking Capability For Microgrids Based On Physics-Informed Reinforcement Learning, Buxin She, Fangxing Li, Hantao Cui, Hang Shuai, Oroghene Oboreh-Snapps, Rui Bo, Nattapat Praisuwanna, Jingxin Wang, Leon M. Tolbert Jan 2023

Inverter Pq Control With Trajectory Tracking Capability For Microgrids Based On Physics-Informed Reinforcement Learning, Buxin She, Fangxing Li, Hantao Cui, Hang Shuai, Oroghene Oboreh-Snapps, Rui Bo, Nattapat Praisuwanna, Jingxin Wang, Leon M. Tolbert

Electrical and Computer Engineering Faculty Research & Creative Works

The increasing penetration of inverter-based resources (IBRs) calls for an advanced active and reactive power (PQ) control strategy in microgrids. To enhance the controllability and flexibility of the IBRs, this paper proposed an adaptive PQ control method with trajectory tracking capability, combining model-based analysis, physics-informed reinforcement learning (RL), and power hardware-in-the-loop (HIL) experiments. First, model-based analysis proves that there exists an adaptive proportional-integral controller with time-varying gains that can ensure any exponential PQ output trajectory of IBRs. These gains consist of a constant factor and an exponentially decaying factor, which are then obtained using a model-free deep reinforcement learning approach …

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Wideband Inverse Matrix For Radiated Two-Stage Mimo Measurements, Jun Li, Bin Lin, Yihong Qi, James L. Drewniak, Jiang Zhu, Daryl G. Beetner Jan 2023

Wideband Inverse Matrix For Radiated Two-Stage Mimo Measurements, Jun Li, Bin Lin, Yihong Qi, James L. Drewniak, Jiang Zhu, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Multiple-input and multiple-output (MIMO) technology is one of the significant components in the growing fifth-generation (5G) communication systems. The 5G system has expanded its frequency range and widened the bandwidth to achieve higher throughput rates and more stable wireless qualities, which brings new challenges to the over-the-air (OTA) MIMO evaluations. The wide bandwidth introduces systematic uncertainties into the MIMO measurement because of the increased amplitude and phase variation issues under different frequencies in the wideband signals, and it could lead to invalid MIMO throughput measurement results when severe. The effect on antenna isolation resulting from amplitude and phase variation in …

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Thermal Diffusivity Materials Characterization Via Active Microwave Thermography, Logan M. Wilcox, Kristen M. Donnell Jan 2023

Thermal Diffusivity Materials Characterization Via Active Microwave Thermography, Logan M. Wilcox, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Active microwave thermography (AMT) is a relatively new nondestructive evaluation method which is proposed in this work for thermal materials characterization. Specifically, AMT is investigated as a single-sided measurement option for out-of-plane thermal diffusivity (a parameter traditionally measured using a two-sided technique). Simulation and measurement results support the use of AMT for such a characterization for materials backed by an electromagnetically absorptive material. Both lossless and lossy materials may be measured, with better accuracy for lossless materials. The effect of heating time was also considered. The results indicate that for the 50 W system used here, 100 seconds of electromagnetic …

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Transformer Leakage Inductance Design Methodology, Angshuman Sharma, Jonathan W. Kimball Jan 2023

Transformer Leakage Inductance Design Methodology, Angshuman Sharma, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

The leakage inductance exhibited by a transformer depends on its winding geometry, which generally involves the selection of several key design parameters in addition to the winding structure and the interleaving configuration. With few resources explaining the effects of these design choices on the observed leakage inductance, numerous trial-and-error iterations become necessary to realize the desired leakage inductance. This paper explores more than a hundred winding geometries feasible in a 2- winding transformer comprising the same magnetic core, number of turns, and wire gauge, and finds the leakage inductance for each unique design using 2-D finite element method (FEM) simulations …

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Interval Analysis Method For The Uncertainty And Sensitivity Characterization In Transmission Line Systems, Ping Yuan, Lijun Jiang Jan 2023

Interval Analysis Method For The Uncertainty And Sensitivity Characterization In Transmission Line Systems, Ping Yuan, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

Uncertainty in electronic fabrication process could cause serious yield issues and stability concerns. Hence, identifying the resultant range caused by the uncertainty in the system is a critical topic in modern EDA design process. Monte Carlo method is considered as a golden standard but with many drawbacks. In the paper, we propose to use the interval analysis (IA) to analyze the signal integrity and power integrity problems in transmission line (TL) systems. Using the interval representing the uncertainty range of parameters in the system, the uncertainty range of the system can be derived by the derived analytical expression. It is …

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Solving Electromagnetic Inverse Scattering Problems In Inhomogeneous Media By Deep Convolutional Encoder-Decoder Structure, Huan Huan Zhang, He Ming Yao, Lijun Jiang, Michael Ng Jan 2023

Solving Electromagnetic Inverse Scattering Problems In Inhomogeneous Media By Deep Convolutional Encoder-Decoder Structure, Huan Huan Zhang, He Ming Yao, Lijun Jiang, Michael Ng

Electrical and Computer Engineering Faculty Research & Creative Works

This communication proposes a novel deep learning (DL) approach to solve electromagnetic inverse scattering (EMIS) problems in inhomogeneous media. The conventional approaches for solving inhomogeneous EMIS problems generally have to consider inhomogeneous Green’s functions or conduct approximation operations to media, which inevitably introduces various challenges, including complex mathematical derivation, high computation cost, unavoidable nonlinearity, and even strong ill-posedness. To avoid these challenges, we propose a DL approach based on the complex-valued deep convolutional neural networks (DConvNets), which comprise the deep convolutional encoder–decoder (DCED) structure. Its training data are collected based on the simple synthetic dataset. While the scattered fields received …

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Lifelong Deep Learning-Based Control Of Robot Manipulators, Irfan Ganie, Jagannathan Sarangapani Jan 2023

Lifelong Deep Learning-Based Control Of Robot Manipulators, Irfan Ganie, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

This study proposes a lifelong deep learning control scheme for robotic manipulators with bounded disturbances. This scheme involves the use of an online tunable deep neural network (DNN) to approximate the unknown nonlinear dynamics of the robot. The control scheme is developed by using a singular value decomposition-based direct tracking error-driven approach, which is utilized to derive the weight update laws for the DNN. To avoid catastrophic forgetting in multi-task scenarios and to ensure lifelong learning (LL), a novel online LL scheme based on elastic weight consolidation is included in the DNN weight-tuning laws. Our results demonstrate that the resulting …

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Rafid: A Lightweight Approach To Radio Frequency Interference Detection In Time Domain Using Lstm And Statistical Analysis, Luke A. Smith, Vishesh Kumar Tanwar, Maciej Jan Zawodniok, Sanjay Kumar Madria Jan 2023

Rafid: A Lightweight Approach To Radio Frequency Interference Detection In Time Domain Using Lstm And Statistical Analysis, Luke A. Smith, Vishesh Kumar Tanwar, Maciej Jan Zawodniok, Sanjay Kumar Madria

Electrical and Computer Engineering Faculty Research & Creative Works

Recently, the utilization of Radio Frequency (RF) devices has increased exponentially over numerous vertical platforms. This rise has led to an abundance of Radio Frequency Interference (RFI) continues to plague RF systems today. The continued crowding of the RF spectrum makes RFI efficient and lightweight mitigation critical. Detecting and localizing the interfering signals is the foremost step for mitigating RFI concerns. Addressing these challenges, we propose a novel and lightweight approach, namely RaFID, to detect and locate the RFI by incorporating deep neural networks (DNNs) and statistical analysis via batch-wise mean aggregation and standard deviation (SD) calculations. RaFID investigates the …

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Continual Learning-Based Optimal Output Tracking Of Nonlinear Discrete-Time Systems With Constraints: Application To Safe Cargo Transfer, Behzad Farzanegan, S. (Sarangapani) Jagannathan Jan 2023

Continual Learning-Based Optimal Output Tracking Of Nonlinear Discrete-Time Systems With Constraints: Application To Safe Cargo Transfer, Behzad Farzanegan, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This Paper Addresses a Novel Lifelong Learning (LL)-Based Optimal Output Tracking Control of Uncertain Non-Linear Affine Discrete-Time Systems (DT) with State Constraints. First, to Deal with Optimal Tracking and Reduce the Steady State Error, a Novel Augmented System, Including Tracking Error and its Integral Value and Desired Trajectory, is Proposed. to Guarantee Safety, an Asymmetric Barrier Function (BF) is Incorporated into the Utility Function to Keep the Tracking Error in a Safe Region. Then, an Adaptive Neural Network (NN) Observer is Employed to Estimate the State Vector and the Control Input Matrix of the Uncertain Nonlinear System. Next, an NN-Based …

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Analysis On Extraction Of Potential Radiated Emission Limit Line For Data Center Equipment From 10 Ghz To 40 Ghz, Zhekun Peng, Wei Zhang, Jong Hwa Kwon, Donghyun Kim Jan 2023

Analysis On Extraction Of Potential Radiated Emission Limit Line For Data Center Equipment From 10 Ghz To 40 Ghz, Zhekun Peng, Wei Zhang, Jong Hwa Kwon, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

The Radiated Emission (RE) Potential Limit Line for Router System is Analyzed from 10 GHz to 40 GHz based on CISPR TR 16-4-4 Standard. Statistical Data is Collected for the Limit Line Extraction from Measurement, Numerical Analysis, 3D Full-Wave Simulation and Literature Studies. All the Factors Considered in Limit Line Calculation Are Analyzed for Data Center Equipment Operation. the Result of Extracted Potential Limit Line Shows the Rising Limit Line between 10 GHz and 40 GHz Frequency Band for Potential Future Radiated Emission Limit Line above 40 GHz Targeted for High-Speed Equipment Radiated Emission. This Paper is Not a Standard …

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Challenges And Solutions For Automotive Ota Testing, Jiyu Wu, Yihong Qi, Penghui Shen, Wei Yu, Lie Liu, James L. Drewniak Jan 2023

Challenges And Solutions For Automotive Ota Testing, Jiyu Wu, Yihong Qi, Penghui Shen, Wei Yu, Lie Liu, James L. Drewniak

Electrical and Computer Engineering Faculty Research & Creative Works

OTA (Over-The-Air) Testing is Essential for Developing Assisted and Autonomous Driving Systems in Vehicles, as It Plays a Crucial Role in the Localization, Perception, and Intelligent Driving Capabilities of ICVs (Intelligent Connected Vehicles). Automotive Antennas, Typically Much Smaller in Size Than the Vehicle itself and Can Be Located in Various Positions, Require Spherical Near-Field Measurement for OTA Testing. While There Are Established Standards for OTA Testing Methods and Uncertainties for Mobile Devices, Base Stations, and Satellite Components, There Are Still Many Challenges in the OTA Testing of Automotive Systems. These Challenges, specifically in SISO (Single Input Single Output) and MIMO …

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Design And Construction Of An Arbitrary Pulse Compressive Amplifier, Cody Goins, Aaron Harmon, Victor Khilkevich, Daryl G. Beetner Jan 2023

Design And Construction Of An Arbitrary Pulse Compressive Amplifier, Cody Goins, Aaron Harmon, Victor Khilkevich, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Compressive Pulse Amplifiers Are a Class of Amplifiers that Convert Long Low Amplitude Signals into Very Broadband Pulses of High Amplitude, Yielding a Very High Instantaneous Peak Power Output Pulse. However, in the Realm of Electronic Immunity and Susceptibility Testing, Very Broadband Short Pulses Are Not Always Desired. This Work Presents a Design for a Compressive Amplifier that is Aimed at Creating Arbitrary Pulsed Signals of Varying Bandwidths. Limitations of the Achievable Gain and Methods Used Are Discussed.

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A Real-Time Microwave Camera Prototype With Zero-Bias Diode Detectors For Emi Source Imaging, Xin Yan, Liang Liu, Victor Khilkevich Jan 2023

A Real-Time Microwave Camera Prototype With Zero-Bias Diode Detectors For Emi Source Imaging, Xin Yan, Liang Liu, Victor Khilkevich

Electrical and Computer Engineering Faculty Research & Creative Works

Emission Source Microscopy (ESM) Could Be Utilized to Localize the Electromagnetic Interference (EMI) Sources that Contribute to the Far-Field Radiation. in Those Cases, the Electrical Field over a Two-Dimensional Plane is Collected by Mechanical Scanning, Resulting in a Long Measurement Time and the Presence of Mechanical Errors. in This Work, a Microwave Camera based on a Two-Dimensional Array of Elliptical Slot Antennas and Diode Detectors is Presented. Multiplexers Are Utilized to Access the Output of Each Detector and the Scanning of the Whole Array Could Be Done Multiple Times Per Second.

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Challenges And Prospects Of Vehicle Ota Spherical Near-Field Measurement Probes, Dao Lin, Zhanghua Cai, Lidong Chi, Fuhai Li, James L. Drewniak, Gang Feng, Yihong Qi Jan 2023

Challenges And Prospects Of Vehicle Ota Spherical Near-Field Measurement Probes, Dao Lin, Zhanghua Cai, Lidong Chi, Fuhai Li, James L. Drewniak, Gang Feng, Yihong Qi

Electrical and Computer Engineering Faculty Research & Creative Works

This Paper Discusses the Issue of Measuring Probe Indicators for Large-Scale Equipment, Such as Automobiles, under Conditions of Offset Configuration. a Simulation of Spherical Near-Field Measurement based on an Offset Configuration is Presented in This Paper. the Measurement Error is Defined According to the Reference Data Calculated by Spherical Wave Expansion Theory. through Comparative Analysis of the Simulation Results, the Main Reason for the Measurement Error is the Insufficient Coverage of the Probe's Beamwidth. by Adjusting the Probe's Radiation Pattern using Simulation Software, an Optimized Probe that Satisfies Near-Field Measurement Requirements under Meter-Level Offset Conditions is Obtained. Finally, based on …

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Lifelong Learning-Based Multilayer Neural Network Control Of Nonlinear Continuous-Time Strict-Feedback Systems, Irfan Ahmad Ganie, S. (Sarangapani) Jagannathan Jan 2023

Lifelong Learning-Based Multilayer Neural Network Control Of Nonlinear Continuous-Time Strict-Feedback Systems, Irfan Ahmad Ganie, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In This Paper, We Investigate Lifelong Learning (LL)-Based Tracking Control for Partially Uncertain Strict Feedback Nonlinear Systems with State Constraints, employing a Singular Value Decomposition (SVD) of the Multilayer Neural Networks (MNNs) Activation Function based Weight Tuning Scheme. the Novel SVD-Based Approach Extends the MNN Weight Tuning to (Formula Presented.) Layers. a Unique Online LL Method, based on Tracking Error, is Integrated into the MNN Weight Update Laws to Counteract Catastrophic Forgetting. to Adeptly Address Constraints for Safety Assurances, Taking into Account the Effects Caused by Disturbances, We Utilize a Time-Varying Barrier Lyapunov Function (TBLF) that Ensures a Uniformly Ultimately …

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Towards Robust Consensus For Intelligent Decision-Making In Iot Blockchain Networks, Charles Rawlins, S. (Sarangapani) Jagannathan Jan 2023

Towards Robust Consensus For Intelligent Decision-Making In Iot Blockchain Networks, Charles Rawlins, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Distributed consensus is the core aspect of blockchain protocol security design. Recent protocols like IOTA have improved concurrency and scalability over Proof-of-work (PoW) with Bitcoin but have core design decisions that are inefficient for limited devices and do not take advantage of previous network experience to reduce calculations. This work proposes the first blockchain consensus protocol based on active machine-learning decisions, called Proof-of-history (PoH). PoH is setup as a distributed reinforcement-learning task for monitoring classification and training of blockchain transactions with an inner deep classifier. Early theoretical analysis and simulations show that PoH is robust to uncoordinated byzantine attacks through …

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Improved Intelligent Ledger Construction For Realistic Iot Blockchain Networks, Charles Rawlins, S. (Sarangapani) Jagannathan Jan 2023

Improved Intelligent Ledger Construction For Realistic Iot Blockchain Networks, Charles Rawlins, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Scalability is essential for next generation blockchain technology to integrate with large mobile networks like Internet of Things (IoT). The IOTA distributed ledger protocol has combined transaction generation and verification to address this, but at the expense of increased reliance on connectivity to resolve conflicts with a novel ledger data structure. Intelligent Ledger Construction (ILC) was proposed as an auditable lightweight reinforcement-learning scheme to address this constraint with proposal of local conflict resolution with machine-learning classification. This effort presents an improved reliability reward model to enhance training for ILC and further reduce adversarial gaming and resource usage. Testing this revision …

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Accelerated Statistical Eye Diagram Estimation Method For Efficient Signal Integrity Analysis, Junyong Park, Youngwoo Kim, Donghyun Kim Jan 2023

Accelerated Statistical Eye Diagram Estimation Method For Efficient Signal Integrity Analysis, Junyong Park, Youngwoo Kim, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

This article proposes an accelerated statistical eye diagram estimation method for efficient signal integrity (SI) analysis. An eye diagram is a critical metric in the SI analysis, however obtaining an eye diagram is time-consuming in simulation. The required time might be a few weeks depending on the complexity. Because the eye diagram is obtained by superposition of the received waveforms. Statistical eye diagram estimation methods were proposed to make the eye diagram acquisition efficient, however, it still has a limited improvement due to a large number of convolution operations. To address this limitation, the proposed method includes two approaches: (i) …

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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 …

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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 …

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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 …

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