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Full-Text Articles in Engineering

Online Parameter Estimation Under Non-Persistent Excitations For High-Rate Dynamic Systems, Jin Yan, Simon Laflamme, Jonathan Hong, Jacob Dodson Dec 2021

Online Parameter Estimation Under Non-Persistent Excitations For High-Rate Dynamic Systems, Jin Yan, Simon Laflamme, Jonathan Hong, Jacob Dodson

Civil, Construction and Environmental Engineering Publications

High-rate dynamic systems are defined as systems experiencing dynamic events of typical amplitudes higher than 100 gn for a duration of less than 100 ms. They are characterized by 1) large uncertainties on the external loads; 2) high levels of nonstationarity and heavy disturbance; and 3) generation of unmodeled dynamics from changes in mechanical configuration. To fully enable these systems, feedback capabilities must be developed. This includes computationally fast software and low latency hardware. This paper presents a pure time-based online parameter estimation algorithm for high-rate dynamic systems with real-time applicability. The algorithm is based on a model reference ...


Array-Based Guided Wave Source Location Using Dispersion Compensation, Andrew Downs, Ronald A. Roberts, Jiming Song Nov 2021

Array-Based Guided Wave Source Location Using Dispersion Compensation, Andrew Downs, Ronald A. Roberts, Jiming Song

Electrical and Computer Engineering Publications

An important advantage of guided waves is their ability to propagate large distances and yield more information about flaws than bulk waves. Unfortunately, the multi-modal, dispersive nature of guided waves makes them difficult to use for locating flaws. In this work, we present a method and experimental data for removing the deleterious effects of multi-mode dispersion allowing for source localization at frequencies comparable to those of bulk waves. Time domain signals are obtained using a novel 64-element phased array and processed to extract wave number and frequency spectra. By an application of Auld’s electro-mechanical reciprocity relation, mode contributions are ...


Motivation Dynamics For Autonomous Composition Of Navigation Tasks, Paul B. Reverdy, Vasileios Vasilopoulos, Daniel E. Koditschek Aug 2021

Motivation Dynamics For Autonomous Composition Of Navigation Tasks, Paul B. Reverdy, Vasileios Vasilopoulos, Daniel E. Koditschek

Departmental Papers (ESE)

We physically demonstrate a reactive sensorimotor architecture for mobile robots whose behaviors are generated by motivation dynamics. Motivation dynamics uses a continuous dynamical system to reactively compose low-level control vector fields using valuation functions which capture the potentially competing influences of external stimuli relative to the system's own internal state. We show that motivation dynamics 1) naturally accommodates external stimuli through standard signal processing tools, and 2) can effectively encode a repetitive higher-level task by composing several low-level controllers to achieve a limit cycle in which the robot repeatedly navigates towards two alternatively valuable goal locations in a commensurately ...


Dynamic Planning Networks, Norman Tasfi, Miriam A M Capretz Jul 2021

Dynamic Planning Networks, Norman Tasfi, Miriam A M Capretz

Electrical and Computer Engineering Publications

We introduce Dynamic Planning Networks (DPN), a novel architecture for deep reinforcement learning, that combines model-based and model-free aspects for online planning. Our architecture learns to dynamically construct plans using a learned state-transition model by selecting and traversing between simulated states and actions to maximize information before acting. DPN learns to efficiently form plans by expanding a single action conditional state transition at a time instead of exhaustively evaluating each action, reducing the number of state-transitions used during planning. We observe emergent planning patterns in our agent, including classical search methods such as breadth-first and depth-first search. DPN shows improved ...


On-Chip Nanoscale Plasmonic Optical Modulators, Abdalrahman Mohamed Nader Abdelhamid Jun 2021

On-Chip Nanoscale Plasmonic Optical Modulators, Abdalrahman Mohamed Nader Abdelhamid

Theses and Dissertations

In this thesis work, techniques for downsizing Optical modulators to nanoscale for the purpose of utilization in on chip communication and sensing applications are explored. Nanoscale optical interconnects can solve the electronics speed limiting transmission lines, in addition to decrease the electronic chips heat dissipation. A major obstacle in the path of achieving this goal is to build optical modulators, which transforms data from the electrical form to the optical form, in a size comparable to the size of the electronics components, while also having low insertion loss, high extinction ratio and bandwidth. Also, lap-on-chip applications used for fast diagnostics ...


Characterization Of Time-Variant And Time-Invariant Assessment Of Suicidality On Reddit Using C-Ssrs, Manas Gaur, Vamsi Aribandi, Amanuel Alambo, Ugur Kursuncu, Krishnaprasad Thirunarayan, Jonathan Beich, Jyotishman Pathak, Amit Sheth May 2021

Characterization Of Time-Variant And Time-Invariant Assessment Of Suicidality On Reddit Using C-Ssrs, Manas Gaur, Vamsi Aribandi, Amanuel Alambo, Ugur Kursuncu, Krishnaprasad Thirunarayan, Jonathan Beich, Jyotishman Pathak, Amit Sheth

Publications

Suicide is the 10th leading cause of death in the U.S (1999-2019). However, predicting when someone will attempt suicide has been nearly impossible. In the modern world, many individuals suffering from mental illness seek emotional support and advice on well-known and easily-accessible social media platforms such as Reddit. While prior artificial intelligence research has demonstrated the ability to extract valuable information from social media on suicidal thoughts and behaviors, these efforts have not considered both severity and temporality of risk. The insights made possible by access to such data have enormous clinical potential - most dramatically envisioned as a trigger ...


Developing A Multimedia Interface For Electrical Biosignal Interpretation, Christopher Cox May 2021

Developing A Multimedia Interface For Electrical Biosignal Interpretation, Christopher Cox

Undergraduate Research and Scholarship Symposium

In the last ten years, a great deal of interest has been generated around the practice of using plants’ electrical signals to create sound or music. In order to render biosignals capable of producing sound electronically, some kind of interface is necessary that converts a plant’s natural electrical signals into data that a computer can understand. Existing commercial interfaces cost at minimum $3001,2 . Worse yet, two popular off-the-shelf interfaces conform their output signals to stereotypical human notions of what a plant might “sound like”. In this project we fabricated a simple but high-performance interface for less than $5 ...


Collaborative City Digital Twin For The Covid-19 Pandemic: A Federated Learning Solution, Junjie Pang, Yan Huang, Zhenzhen Xie, Jianbo Li, Zhipeng Cai May 2021

Collaborative City Digital Twin For The Covid-19 Pandemic: A Federated Learning Solution, Junjie Pang, Yan Huang, Zhenzhen Xie, Jianbo Li, Zhipeng Cai

Tsinghua Science and Technology

The novel coronavirus, COVID-19, has caused a crisis that affects all segments of the population. As the knowledge and understanding of COVID-19 evolve, an appropriate response plan for this pandemic is considered one of the most effective methods for controlling the spread of the virus. Recent studies indicate that a city Digital Twin (DT) is beneficial for tackling this health crisis, because it can construct a virtual replica to simulate factors, such as climate conditions, response policies, and people’s trajectories, to help plan efficient and inclusive decisions. However, a city DTsystem relies on long-term and high-quality data collection to ...


A Data-Driven Clustering Recommendation Method For Single-Cell Rna-Sequencing Data, Yu Tian, Ruiqing Zheng, Zhenlan Liang, Suning Li, Fang-Xiang Wu, Min Li May 2021

A Data-Driven Clustering Recommendation Method For Single-Cell Rna-Sequencing Data, Yu Tian, Ruiqing Zheng, Zhenlan Liang, Suning Li, Fang-Xiang Wu, Min Li

Tsinghua Science and Technology

Recently, the emergence of single-cell RNA-sequencing (scRNA-seq) technology makes it possible to solve biological problems at the single-cell resolution. One of the critical steps in cellular heterogeneity analysis is the cell type identification. Diverse scRNA-seq clustering methods have been proposed to partition cells into clusters. Among all the methods, hierarchical clustering and spectral clustering are the most popular approaches in the downstream clustering analysis with different preprocessing strategies such as similarity learning, dropout imputation, and dimensionality reduction. In this study, we carry out a comprehensive analysis by combining different strategies with these two categories of clustering methods on scRNA-seq datasets ...


A Computer-Aided System For Ocular Myasthenia Gravis Diagnosis, Guanjie Liu, Yan Wei, Yunshen Xie, Jianqiang Li, Liyan Qiao, Ji-Jiang Yang May 2021

A Computer-Aided System For Ocular Myasthenia Gravis Diagnosis, Guanjie Liu, Yan Wei, Yunshen Xie, Jianqiang Li, Liyan Qiao, Ji-Jiang Yang

Tsinghua Science and Technology

The current mode of clinical aided diagnosis of Ocular Myasthenia Gravis (OMG) is time-consuming and laborious, and it lacks quantitative standards. An aided diagnostic system for OMG is proposed to solve this problem. The values calculated by the system include three clinical indicators: eyelid distance, sclera distance, and palpebra superior fatigability test time. For the first two indicators, the semantic segmentation method was used to extract the pathological features of the patient’s eye image and a semantic segmentation model was constructed. The patient eye image was divided into three regions: iris, sclera, and background. The indicators were calculated based ...


Robust Segmentation Method For Noisy Images Based On An Unsupervised Denosing Filter, Ling Zhang, Jianchao Liu, Fangxing Shang, Gang Li, Juming Zhao, Yueqin Zhang May 2021

Robust Segmentation Method For Noisy Images Based On An Unsupervised Denosing Filter, Ling Zhang, Jianchao Liu, Fangxing Shang, Gang Li, Juming Zhao, Yueqin Zhang

Tsinghua Science and Technology

Level-set-based image segmentation has been widely used in unsupervised segmentation tasks. Researchers have recently alleviated the influence of image noise on segmentation results by introducing global or local statistics into existing models. Most existing methods are based on the assumption that the distribution of image noise is known or observable. However, real-time images do not meet this assumption. To bridge this gap, we propose a novel level-set-based segmentation method with an unsupervised denoising mechanism. First, a denoising filter is acquired under the unsupervised learning paradigm. Second, the denoising filter is integrated into the level-set framework to separate noise from the ...


Efficient Scheduling Mapping Algorithm For Row Parallel Coarse-Grained Reconfigurable Architecture, Naijin Chen, Zhen Wang, Ruixiang He, Jianhui Jiang, Fei Cheng, Chenghao Han May 2021

Efficient Scheduling Mapping Algorithm For Row Parallel Coarse-Grained Reconfigurable Architecture, Naijin Chen, Zhen Wang, Ruixiang He, Jianhui Jiang, Fei Cheng, Chenghao Han

Tsinghua Science and Technology

Row Parallel Coarse-Grained Reconfigurable Architecture (RPCGRA) has the advantages of maximum parallelism and programmable flexibility. Designing an efficient algorithm to map the diverse applications onto RPCGRA is difficult due to a number of RPCGRA hardware constraints. To solve this problem, the nodes of the data flow graph must be partitioned and scheduled onto the RPCGRA. In this paper, we present a Depth-First Greedy Mapping (DFGM) algorithm that simultaneously considers the communication costs and the use times of the Reconfigurable Cell Array (RCA). Compared with level breadth mapping, the performance of DFGM is better. The percentage of maximum improvement in the ...


Game Theoretical Approach For Non-Overlapping Community Detection, Baohua Sun, Richard Al-Bayaty, Qiuyuan Huang, Dapeng Wu May 2021

Game Theoretical Approach For Non-Overlapping Community Detection, Baohua Sun, Richard Al-Bayaty, Qiuyuan Huang, Dapeng Wu

Tsinghua Science and Technology

Graph clustering, i.e., partitioning nodes or data points into non-overlapping clusters, can be beneficial in a large varieties of computer vision and machine learning applications. However, main graph clustering schemes, such as spectral clustering, cannot be applied to a large network due to prohibitive computational complexity required. While there exist methods applicable to large networks, these methods do not offer convincing comparisons against known ground truth. For the first time, this work conducts clustering algorithm performance evaluations on large networks (consisting of one million nodes) with ground truth information. Ideas and concepts from game theory are applied towards graph ...


Inertial Motion Tracking On Mobile And Wearable Devices: Recent Advancements And Challenges, Zhipeng Song, Zhichao Cao, Zhenjiang Li, Jiliang Wang, Yunhao Liu May 2021

Inertial Motion Tracking On Mobile And Wearable Devices: Recent Advancements And Challenges, Zhipeng Song, Zhichao Cao, Zhenjiang Li, Jiliang Wang, Yunhao Liu

Tsinghua Science and Technology

Motion tracking via Inertial Measurement Units (IMUs) on mobile and wearable devices has attracted significant interest in recent years. High-accuracy IMU-tracking can be applied in various applications, such as indoor navigation, gesture recognition, text input, etc. Many efforts have been devoted to improving IMU-based motion tracking in the last two decades, from early calibration techniques on ships or airplanes, to recent arm motion models used on wearable smart devices. In this paper, we present a comprehensive survey on IMU-tracking techniques on mobile and wearable devices. We also reveal the key challenges in IMU-based motion tracking on mobile and wearable devices ...


Deep Reinforcement Learning Based Mobile Robot Navigation: A Review, Kai Zhu, Tao Zhang May 2021

Deep Reinforcement Learning Based Mobile Robot Navigation: A Review, Kai Zhu, Tao Zhang

Tsinghua Science and Technology

Navigation is a fundamental problem of mobile robots, for which Deep Reinforcement Learning (DRL) has received significant attention because of its strong representation and experience learning abilities. There is a growing trend of applying DRL to mobile robot navigation. In this paper, we review DRL methods and DRL-based navigation frameworks. Then we systematically compare and analyze the relationship and differences between four typical application scenarios: local obstacle avoidance, indoor navigation, multi-robot navigation, and social navigation. Next, we describe the development of DRL-based navigation. Last, we discuss the challenges and some possible solutions regarding DRL-based navigation.


Decomposition-Based Multi-Objective Optimization For Energy-Aware Distributed Hybrid Flow Shop Scheduling With Multiprocessor Tasks, Enda Jiang, Ling Wang, Jingjing Wang May 2021

Decomposition-Based Multi-Objective Optimization For Energy-Aware Distributed Hybrid Flow Shop Scheduling With Multiprocessor Tasks, Enda Jiang, Ling Wang, Jingjing Wang

Tsinghua Science and Technology

This paper addresses the Energy-Aware Distributed Hybrid Flow Shop Scheduling Problem with Multiprocessor Tasks (EADHFSPMT) by considering two objectives simultaneously, i.e., makespan and total energy consumption. It consists of three sub-problems, i.e., job assignment between factories, job sequence in each factory, and machine allocation for each job. We present a mixed inter linear programming model and propose a Novel Multi-Objective Evolutionary Algorithm based on Decomposition (NMOEA/D). We specially design a decoding scheme according to the characteristics of the EADHFSPMT. To initialize a population with certain diversity, four different rules are utilized. Moreover, a cooperative search is designed ...


Towards "General Purpose" Brain-Inspired Computing System, Youhui Zhang, Peng Qu, Weimin Zheng May 2021

Towards "General Purpose" Brain-Inspired Computing System, Youhui Zhang, Peng Qu, Weimin Zheng

Tsinghua Science and Technology

Brain-inspired computing refers to computational models, methods, and systems, that are mainly inspired by the processing mode or structure of brain. A recent study proposed the concept of "neuromorphic completeness" and the corresponding system hierarchy, which is helpful to determine the capability boundary of brain-inspired computing system and to judge whether hardware and software of brain-inspired computing are compatible with each other. As a position paper, this article analyzes the existing brain-inspired chips’ design characteristics and the current so-called "general purpose" application development frameworks for brain-inspired computing, as well as introduces the background and the potential of this proposal. Further ...


Distributed Scheduling Problems In Intelligent Manufacturing Systems, Yaping Fu, Yushuang Hou, Zifan Wang, Xinwei Wu, Kaizhou Gao, Ling Wang May 2021

Distributed Scheduling Problems In Intelligent Manufacturing Systems, Yaping Fu, Yushuang Hou, Zifan Wang, Xinwei Wu, Kaizhou Gao, Ling Wang

Tsinghua Science and Technology

Currently, manufacturing enterprises face increasingly fierce market competition due to the various demands of customers and the rapid development of economic globalization. Hence, they have to extend their production mode into distributed environments and establish multiple factories in various geographical locations. Nowadays, distributed manufacturing systems have been widely adopted in industrial production processes. In recent years, many studies have been done on the modeling and optimization of distributed scheduling problems. This work provides a literature review on distributed scheduling problems in intelligent manufacturing systems. By summarizing and evaluating existing studies on distributed scheduling problems, we analyze the achievements and current ...


Multi-Agent Modeling And Simulation In The Ai Age, Wenhui Fan, Peiyu Chen, Daiming Shi, Xudong Guo, Li Kou May 2021

Multi-Agent Modeling And Simulation In The Ai Age, Wenhui Fan, Peiyu Chen, Daiming Shi, Xudong Guo, Li Kou

Tsinghua Science and Technology

With the rapid development of artificial intelligence (AI) technology and its successful application in various fields, modeling and simulation technology, especially multi-agent modeling and simulation (MAMS), of complex systems has rapidly advanced. In this study, we first describe the concept, technical advantages, research steps, and research status of MAMS. Then we review the development status of the hybrid modeling and simulation combining multi-agent and system dynamics, the modeling and simulation of multi-agent reinforcement learning, and the modeling and simulation of large-scale multi-agent. Lastly, we introduce existing MAMS platforms and their comparative studies. This work summarizes the current research situation of ...


Convergence Of Broadband And Broadcast/Multicast In Maritime Information Networks, Jun Du, Jian Song, Yong Ren, Jintao Wang May 2021

Convergence Of Broadband And Broadcast/Multicast In Maritime Information Networks, Jun Du, Jian Song, Yong Ren, Jintao Wang

Tsinghua Science and Technology

Recently, the fifth-generation (5G) of wireless networks mainly focuses on the terrestrial applications. However, the well-developed emerging technologies in 5G are hardly applied to the maritime communications, resulting from the lack of communication infrastructure deployed on the vast ocean, as well as different characteristics of wireless propagation environment over the sea and maritime user distribution. To satisfy the expected plethora of broadband communications and multimedia applications on the ocean, a brand-new maritime information network with a comprehensive coverage capacity in terms of all-hour, all-weather, and all-sea-area has been expected as a revolutionary paradigm to extend the terrestrial capacity of enhanced ...


Ambipolar Transport Compact Models For Two-Dimensional Materials Based Field-Effect Transistors, Zhaoyi Yan, Guangyang Gou, Jie Ren, Fan Wu, Yang Shen, He Tian, Yi Yang May 2021

Ambipolar Transport Compact Models For Two-Dimensional Materials Based Field-Effect Transistors, Zhaoyi Yan, Guangyang Gou, Jie Ren, Fan Wu, Yang Shen, He Tian, Yi Yang

Tsinghua Science and Technology

Three main ambipolar compact models for Two-Dimensional (2D) materials based Field-Effect Transistors (2D-FETs) are reviewed: (1) Landauer model, (2) 2D Pao-Sah model, and (3) virtual Source Emission-Diffusion (VSED) model. For the Landauer model, the Gauss quadrature method is applied, and it summarizes all kinds of variants, exhibiting its state-of-art. For the 2D Pao-Sah model, the aspects of its theoretical fundamentals are rederived, and the electrostatic potentials of electrons and holes are clarified. A brief development history is compiled for the VSED model. In summary, the Landauer model is naturally appropriate for the ballistic transport of short channels, and the 2D ...


Design And Tool Flow Of A Reconfigurable Asynchronous Neural Network Accelerator, Jilin Zhang, Hui Wu, Weijia Chen, Shaojun Wei, Hong Chen May 2021

Design And Tool Flow Of A Reconfigurable Asynchronous Neural Network Accelerator, Jilin Zhang, Hui Wu, Weijia Chen, Shaojun Wei, Hong Chen

Tsinghua Science and Technology

Convolutional Neural Networks (CNNs) are widely used in computer vision, natural language processing, and so on, which generally require low power and high efficiency in real applications. Thus, energy efficiency has become a critical indicator of CNN accelerators. Considering that asynchronous circuits have the advantages of low power consumption, high speed, and no clock distribution problems, we design and implement an energy-efficient asynchronous CNN accelerator with a 65 nm Complementary Metal Oxide Semiconductor (CMOS) process. Given the absence of a commercial design tool flow for asynchronous circuits, we develop a novel design flow to implement Click-based asynchronous bundled data circuits ...


Assessment Of Cardiorespiratory Interactions During Life Threatening Events In Preterm Infants Using Point Process And Bivariate Algorithms, Mohammed T. Alenazi May 2021

Assessment Of Cardiorespiratory Interactions During Life Threatening Events In Preterm Infants Using Point Process And Bivariate Algorithms, Mohammed T. Alenazi

Electrical Engineering Theses

Cardiorespiratory interactions considered as an important indicator of neurodevelopment of preterm infants. The strength of cardiorespiratory interactions are presumed to be weak and rapidly fluctuating. The current signal processing algorithms are insufficient to capture such time varying weak interactions. In addition, detection of these interactions becomes difficult during life threatening events due to lack of information available due to apnea (absence of output from respiratory system) and the transient temporal destabilization of cardiac system due to bradycardia. To detect the cardiorespiratory interactions, a point process algorithm of cardiac system with respiration as covariates is proposed. The bivariate model is embedded ...


On The Use Of Hybrid Cfie-Efie For Objects Containing Closed-Open Surface Junctions, Jinbo Liu, Jin Yuan, Wen Luo, Zengrui Li, Jiming Song May 2021

On The Use Of Hybrid Cfie-Efie For Objects Containing Closed-Open Surface Junctions, Jinbo Liu, Jin Yuan, Wen Luo, Zengrui Li, Jiming Song

Electrical and Computer Engineering Publications

To effectively solve the electromagnetic scattering or radiation properties from the perfect electric conductor (PEC) objects containing closed-open surface junctions, how to establish the hybrid combined field integral equation-electric field integral equation (CFIE-EFIE) is studied, which is different with the existing scheme for the objects where the closed and open parts are separate. Further, it is found that when the integral equation is solved using the method of moments (MoM), if the widely used RWG basis functions are employed to expand the induced surface current, the CFIE-EFIE may give inaccurate numerical results for the objects containing fine structures. The numerical ...


Development Of A Two-Level Warping Algorithm And Its Application To Speech Signal Processing, Al-Waled H. Al-Dulaimi May 2021

Development Of A Two-Level Warping Algorithm And Its Application To Speech Signal Processing, Al-Waled H. Al-Dulaimi

All Graduate Theses and Dissertations

In many different fields there are signals that need to be aligned or “warped” in order to measure the similarity between them. When two time signals are compared, or when a pattern is sought in a larger stream of data, it may be necessary to warp one of the signals in a nonlinear way by compressing or stretching it to fit the other. Simple point-to-point comparison may give inadequate results, because one part of the signal might be comparing different relative parts of the other signal/pattern. Such cases need some sort of alignment todo the comparison. Dynamic Time Warping ...


Reactive Planning For Mobile Manipulation Tasks In Unexplored Semantic Environments, Vasileios Vasilopoulos, Yiannis Kantaros, George J. Pappas, Daniel E. Koditschek May 2021

Reactive Planning For Mobile Manipulation Tasks In Unexplored Semantic Environments, Vasileios Vasilopoulos, Yiannis Kantaros, George J. Pappas, Daniel E. Koditschek

Departmental Papers (ESE)

Complex manipulation tasks, such as rearrangement planning of numerous objects, are combinatorially hard problems. Existing algorithms either do not scale well or assume a great deal of prior knowledge about the environment, and few offer any rigorous guarantees. In this paper, we propose a novel hybrid control architecture for achieving such tasks with mobile manipulators. On the discrete side, we enrich a temporal logic specification with mobile manipulation primitives such as moving to a point, and grasping or moving an object. Such specifications are translated to an automaton representation, which orchestrates the physical grounding of the task to mobility or ...


Thruster Communication For Subsurface Environments; Turning Waste Noise Into Useful Data, Stephen Cronin May 2021

Thruster Communication For Subsurface Environments; Turning Waste Noise Into Useful Data, Stephen Cronin

PhD Dissertations and Master's Theses

Acoustic communication serves as one of the primary means of wirelessly communicating underwater. Whereas much of the developments in the field of wireless communication have focused on radio frequency technology, water highly absorbs radio waves rendering the link not feasible for most all subsurface operations. While acoustic links have enabled new capabilities for systems operating in this challenging environment, it has yet to reach the commodity availability of radio systems, meaning that an entire class of small, low-cost systems have been unable to make use of these links. The systems in question are primarily autonomous underwater vehicles (AUVs), as they ...


Impact Of Wind Generation On Transmission Voltage Support During Weak Grid, Yugo Isogai May 2021

Impact Of Wind Generation On Transmission Voltage Support During Weak Grid, Yugo Isogai

Electrical Engineering Undergraduate Honors Theses

Today, there are concerns about the effects of high wind penetration on electric power system operations. This is due to the more distributed nature of wind turbine generation and the corresponding multi-path power flows on the electric power transmission grid. In particular, the higher line impendences associated with inverter-based wind generation results in larger voltage fluctuation under varying load. This may results in conditions where even after a fault condition has been cleared, the transmission system voltages may not recover. Therefore, this paper concentrates on the impact of weak grid condition for voltage instability. To approach it, a 6-bus system ...


Data Forgery Detection In Automatic Generation Control: Exploration Of Automated Parameter Generation And Low-Rate Attacks, Yatish R. Dubasi May 2021

Data Forgery Detection In Automatic Generation Control: Exploration Of Automated Parameter Generation And Low-Rate Attacks, Yatish R. Dubasi

Computer Science and Computer Engineering Undergraduate Honors Theses

Automatic Generation Control (AGC) is a key control system utilized in electric power systems. AGC uses frequency and tie-line power flow measurements to determine the Area Control Error (ACE). ACE is then used by the AGC to adjust power generation and maintain an acceptable power system frequency. Attackers might inject false frequency and/or tie-line power flow measurements to mislead AGC into falsely adjusting power generation, which can harm power system operations. Various data forgery detection models are studied in this thesis. First, to make the use of predictive detection models easier for users, we propose a method for automated ...


Design Of Control Logic And The Human-Machine Interface For A Demonstration Plant Growth Chamber Implemented On A Programmable Logic Controller, Rachael Koehler May 2021

Design Of Control Logic And The Human-Machine Interface For A Demonstration Plant Growth Chamber Implemented On A Programmable Logic Controller, Rachael Koehler

Biological and Agricultural Engineering Undergraduate Honors Theses

This honors thesis covers the planning, development, and implementation of system controls and human-machine interface (HMI) for a demonstration plant growth chamber. The work is a continuation of an ongoing project to be used as an educational and recruiting tool manifesting the skills acquired from the Biological and Agricultural Engineering Department at the University of Arkansas’ College of Engineering. This work includes emergency controls, overall design interface, and controls for both the aeration and lighting subsystems of the growth chamber. Overall design interface controls established included development of two user modes, Administrator and Visitor. The Administrator user will have full ...