Electrical and Computer Engineering Commons^™

Safe Control Design For Quadruped Locomotion In Unstructured Environments Using Linear Transfer Operators, Sriram Sundar Krishnamoorthy Shankara Narayanan

All Dissertations

Deploying quadruped robots in unstructured, obstacle-rich environments requires control and planning methods that remain safe and reliable despite complex terrain geometry, limited sensing, and inevitable modeling errors. This thesis develops operator-theoretic tools for safe control design of robotic systems using linear transfer operators, with a focus on quadruped locomotion in unstructured environments. The central goal is to develop a unified operator-theoretic framework for safe control design based on the Perron–Frobenius (P–F) and Koopman operators. In particular, the thesis leverages \emph{density functions} to develop safe navigation frameworks in the dual space of densities. In the operator-theoretic perspective, the P–F operator governs …

Versatile Exoskeleton Control Paradigms For Agile Human Locomotion: Task-Agnostic And Stability-Augmented Assistance, Miao Yu

All Dissertations

Lower-limb exoskeletons have shown great potential for assisting human locomotion, but designing controllers that provide assistance across diverse locomotor tasks and under external perturbations remains a major challenge. Many existing controllers for steady-state walking rely on pre-defined reference trajectories, which constrain voluntary human motion and limit adaptability across tasks. Moreover, they usually assume stable walking, while their performance under unstable conditions remains largely unexplored. In addition, existing gait stability augmentation controllers are often reactive rather than proactive to unstable conditions. In this dissertation, we propose control frameworks that preserve voluntary human motion while addressing two major challenges: providing task-agnostic assistance …

Learning Global Context For Sparse Activity Recognition In Lengthy Recordings With Limited Dataset Size, Zeyu Tang

All Dissertations

This dissertation describes methods to analyze lengthy recordings of data in order to detect sparsely occurring activities. The narrative below describes the progression of research that led to the development of these methods and their generalization into a unified framework. My research started with designing models for dietary monitoring, including detecting meals from day-long recordings and detecting intake gestures from meal-length recordings. Both tasks share some common characteristics: (a) the target event takes only a small portion of data recordings, and (b) there is global context within full-length data recordings that can help a model make better decisions. After finishing …

A Low Power Fpga Compute Array For Machine Learning And Artificial Intelligence Applications, Todd Wilson

All Graduate Theses and Dissertations, Fall 2023 to Present

Modern small satellites often lack the ability to analyze their data in real time, relying instead on downlinking raw measurements to Earth before any scientific interpretation can occur. This delay restricts missions that require rapid awareness of environmental or space-weather events. This thesis presents the Low-power Array for Cubesat Edge Computing Architecture, Algorithms, and Applications (LACE-C3A), a hardware platform designed to enable in-orbit data processing within the power and volume limits of CubeSat-class spacecraft. 

LACE-C3A uses a modular cluster of flash-based FPGAs, which offer low power consumption, radiation resilience, and in-flight reconfigurability. The system consists of a Controller board responsible …

Reconfigurable Antennas Using Varactors On A Planar Parasitic Layer And Pin Diodes On A Dome Parasitic Layer, Andrew J. Hendricks

All Graduate Theses and Dissertations, Fall 2023 to Present

This research explores two types of reconfigurable, steerable antennas. These antennas change their beam direction based on electric input signals. The antennas have a layer that overlays the main antenna circuit board. The layer has small copper rectangles (pixels) that may be connected using either varactor diodes (which behave as voltage-controlled capacitors) or PIN diodes (electronic switches). The first antenna can steer in the xz-plane in any direction within about 23° from boresight (straight up from the antenna) and in the yz-plane to about 29° from boresight. The antenna uses varactor diodes on a planar layer. The second …

Dynamic Load Assessment Of Pem Fuel Cell Systems Under Pid-Based Control Strategies For Sustainable Operation, Tarek Abedin, Paw, Normy Norfiza Abdul Razak, Chen Chai Phing, Yaw Chong Tak, Monowar Mahmud, Manzoore Elahi M. Soudagar, T. M. Yunus Khan, Mohammad Tariqul Islam, Mohammad Nur-E-Alam

Research outputs 2022 to 2026

Proton exchange membrane fuel cell (PEMFC) systems’ reliable operation under variable load conditions is a significant challenge because of voltage fluctuations, transient variations, and the high computational requirements of sophisticated control techniques like intelligent and model predictive controllers. Even while these state-of-the-art methods provide great precision, complexity and cost often limit their real-time applicability, underscoring the need for a simpler but efficient control solution. To achieve effective voltage regulation in PEMFC systems, this study suggests a DC–DC buck converter in conjunction with a comparator-based proportional–integral–derivative (PID) control technique. In order to provide stable operation under both constant and changing load …

A Low-Cost Motion Classification System For A Stuffed Animal Using An Imu And Machine Learning, Rachel N. Guynes

Honors Theses

One of the many fields that has seen the integration of robots is therapy. Zoomorphic robots (ZR) are designed to look and behave like animals to assist in Animal Assisted Therapy (AAT) practices. Studies show that ZRs can provide benefits similar to working with an actual animal; however, their high cost limits their accessibility. This thesis documents the process of building a real-time, low-cost motion classification system that can be attached to a stuffed animal to make it more interactive. Using a Random Forest (RF) classifier, the system identifies movements with approximately 81.67% accuracy.

Increasing The Prediction Accuracy Of Plant Oil Production Processes Through Adjusting The Parameters Of Machine Learning Models, Umidjon Ruziev, M.K. Shodiev, A.T. Rajabov

Chemical Technology, Control and Management

Vegetable oil production is characterized by high variability in output indicators due to nonlinear interactions between raw material parameters, equipment modes, and heat and mass transfer conditions. Existing approaches to applying machine learning in this field, as a rule, do not account for the impact of hyperparameter adjustments on forecasting quality across specific technological stages. The article presents a systematic methodology for adjusting model parameters (Ridge regression, SVR, GBM, LSTM) applied to three key tasks: predicting residual oil content in oil cake, color index during bleaching, and free fatty acid content during deodorization. In a set of 1000 observations, including …

Intelligent Manufacturing Of Edible Oil: From Smart Sensing To Big Data Platform, Ru Jiang, Nadirbek Yusupbekov

Chemical Technology, Control and Management

With the rapid advancement of Industry 4.0 technologies, intelligent manufacturing and big data platforms are profoundly transforming the production models of the traditional edible oil industry. The edible oil production process involves multiple complex unit operations such as refining, decolorization, and deodorization, which impose high requirements on process control and product quality monitoring. This paper presents a systematic review of key technological advances in the field of intelligent manufacturing of edible oil, establishing a comprehensive technical framework encompassing four dimensions: smart sensing, artificial intelligence applications, IoT communication, and big data platforms. The review begins by analyzing the global background and …

Reliability Analysis Of Separator Control Systems, D.P. Muxitdinov, O.U. Sattarov, M.Sh. Nematov

Chemical Technology, Control and Management

This article aims to enhance the reliability, efficiency, and diagnostic capabilities of gas-liquid separators operating in hazardous technological processes. In the study, the separator is considered as a critical functional unit of an industrial system and is analyzed through structural and functional decomposition. The main operating parameters of the separator, including pressure drop (ΔP), separation efficiency and operational state are described on the basis of a mathematical model. In addition, a state model is developed for normal operation, foaming, liquid droplet carryover with the gas flow, and failure conditions. Emphasis is placed on diagnostic and monitoring issues, …

Data-Driven Neuro-Fuzzy Modeling And Rule Optimization For Intelligent Prediction Of Bioreactor Dynamics, Kamala Najaf Mammadzada

Chemical Technology, Control and Management

Modeling wastewater bioreactors is a challenging problem in environmental engineering because the processes are constantly changing and the microorganisms do not behave in a linear or predictable way. This makes it difficult to predict and control the system behavior. This research investigates three artificial intelligence approaches for modeling wastewater bioreactors: the Mamdani Fuzzy Inference System (FIS), the Adaptive Neuro-Fuzzy Inference System (ANFIS), and clustering-based fuzzy models. These models help us predict what is happening in the bioreactors. For instance they help us predict how the amount of substances in the water is changing over time like dS₀/dt dSs/dt …

Analysis Of Automatic Control Of The Channels And Ditches Cleaning Mechanism Based On Dynamic Indicators, Nasiba Siraj Amirbayova

Chemical Technology, Control and Management

The article deals with the automated design and experimental investigation of reinforced concrete irrigation channels and ditches, their interrelated channel-cleaning mechanisms, which are complex mechatronic systems integrating hydraulic, mechanical, and electronic components. A thorough methodology is suggested, hydrodynamic modeling, combining parametric analysis, and information-based design support to enhance channel concrete cover thickness, geometry, and cleaning system performance. Main structural parameters—involving channel depth, slope, bottom width, and concrete cover—are systematically defined and shown in matrix form to facilitate automated calculation and decision-making. Experimental prototypes and Solid Edge-based digital models are employed to verify the methodology, revealing vital interdependencies between structural parameters, …

Regular Synthesis Algorithms Of Control Devices In Nonlinear Control Systems, Husan Zakirovich Igamberdiyev, Iskandar Yusupovich Abdurakhmanov, Uktam Farkhodovich Mamirov

Chemical Technology, Control and Management

This paper examines the development of regularized algorithms for synthesizing control devices in control systems for polynomial objects, described by multidimensional Volterra functional series. The synthesis problem is solved using a two-stage procedure. In the first stage, the optimization problem is initially solved for an open-loop system. The second stage involves determining the parameters of the control device, i.e., its impulse response functions, by using the relationship between the characteristics of the open-loop and closed-loop systems. Regular algorithms are presented for finding the impulse response functions of the control device based on methods for regularizing the solution of operator equations …

Rdm Interval Arithmetic Based Weapon System Evaluation, Konul Imran Jabbarova Phd

Chemical Technology, Control and Management

For solving this issue, the paper considers a hierarchical multi-criteria decision-making problem, where the choice of a company that corresponds best to the criteria is required. Data used in this problem are presented in the form of intervals, which makes it possible to cope with uncertainty in the problem solution. Several companies working in missile production industry are chosen as alternatives for analysis. Evaluation of the selected alternatives is made based on five criteria clusters. More than twenty criteria are taken into account during evaluation.

Solving this problem is achieved with the help of the technique based on computation of …

Structural Decomposition-Based Control Synthesis For Multivariable Systems Using Oblique Projection Operators, Abdukaxxarov Inomjon Ilxom Ugli Mr, Oripjon Olimovich Zaripov, Jasur Usmonovich Sevinov

Chemical Technology, Control and Management

This paper proposes a novel approach to control synthesis for multivariable systems with algebraic constraints using oblique projection operators and their structural decomposition. The method transforms a standard control law into a structured form by decomposing the control input into constraint-satisfying and null-space components. A generalized oblique projector is constructed using a dual matrix, ensuring flexibility in shaping system properties. Furthermore, a recursive decomposition algorithm is developed, allowing the global projector to be represented as a sum of local operators corresponding to subsystem structures. The proposed framework enables modular control design, decoupling of interactions, and efficient implementation for large-scale systems. …

Conceptual Model For Protecting Personal Data By Depersonalization In Information Systems: Principles, Components, And Life Cycle, Zarina Ildarovna Azizova

Chemical Technology, Control and Management

This article presents a systematic approach to personal data protection through depersonalization in the context of regulatory pressure and growing cyber threats. It proposes a comprehensive conceptual model that formalizes the de-identification process as a manageable sequence of steps, from attribute classification and method selection to mandatory verification of the result. The article also provides a comparative analysis of existing depersonalization methods in terms of their applicability within the proposed model. The model serves as a basis for the development of specific algorithms, as demonstrated by the example of a data shuffling approach.

Efficient Energy Management In Networked Microgrids Using Multi-Agent Deep Reinforcement Learning In The Presence Of Uncertainties, Ayodele Benjamin Chukwuyem

Thesis/ Dissertation Defenses

Microgrid technology is essential in facilitating the transition to smart energy grids in developed countries and mitigating energy poverty in developing countries, particularly in areas where grid extensions are not feasible. Recently, the concept of networked microgrids (NMGs) has garnered tremendous attention due to the plausibility of interactions among interconnected microgrids leading to power networks that are more resilient, reliable, and stable. However, because each microgrid has diverse distributed generation resources (renewables and controllable generators) and each microgrid operator (MO) has different objectives, coordinated energy management is required to satisfy local and system-wide goals under conditions with significant uncertainty. Existing …

The Pid-Based Three Quadcopter Uavs Formation Control Under External Disturbance, Vo Van An, Trinh Luong Mien

Makara Journal of Technology

This paper presents the design and evaluation of a formation control strategy for three quadcopter UAVs, based on a PID controller in a leader–follower structure, under the influence of external disturbances. Each UAV employs a six-degree of-freedom dynamic model and utilises a cascade PID control architecture, in which the inner control loop stabilises the attitude. In contrast, the outer control loop regulates position and maintains the formation. The PID parameters are tuned using the Ziegler–Nichols method to ensure simple implementation and low computational cost. The performance of the control system is evaluated through simulations in the MATLAB environment for two …

A Low-Noise And High-Gain Integrated Photoplethysmography Sensor For Continuous Vital Signs Monitoring, Neethu Mohan

Thesis/ Dissertation Defenses

Photoplethysmography (PPG) sensing is an important technology used for measuring health parameters like, heart rate, respiratory rate, blood oxygen saturation, and blood pressure (BP). The PPG sensing is used for individuals who have to periodically monitor their health due to chronic health conditions. The basic requirements of a wearable PPG sensor include non-invasiveness, prolonged battery life, and being user-friendly. These type of sensors have great demand in the healthcare applications and there is a significant rise in the demand of these sensors. The basic objective of these PPG sensors is to make the continuous vital health monitoring easier without the …

Wavetable Modification In Frequency Domain: Fourier Analysis With Matlab Implementation, Caleb Kortens

Senior Honors Theses

One of the challenges in creating computer generated music is producing life-like sounds. Music produced through computer synthesis can often sound thin and synthetic rather than vibrant and energetic. Wavetable synthesis is a method of waveform generation that uses a wavetable, which is a set of single period waves, or frames, that have varying characteristics. This method allows a synthesizer to transition between waveforms to produce a sound with time varying tone and harmonic characteristics. This adds life and movement to computer generated sounds. Wavetable synthesis is often used to imitate actual instruments, but unique wavetables can be created that …